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The Best Textbooks on Every Subject

167 Post author: lukeprog 16 January 2011 08:30AM

For years, my self-education was stupid and wasteful. I learned by consuming blog posts, Wikipedia articles, classic texts, podcast episodes, popular books, video lectures, peer-reviewed papers, Teaching Company courses, and Cliff's Notes. How inefficient!

I've since discovered that textbooks are usually the quickest and best way to learn new material. That's what they are designed to be, after all. Less Wrong has often recommended the "read textbooks!" method. Make progress by accumulation, not random walks.

But textbooks vary widely in quality. I was forced to read some awful textbooks in college. The ones on American history and sociology were memorably bad, in my case. Other textbooks are exciting, accurate, fair, well-paced, and immediately useful.

What if we could compile a list of the best textbooks on every subject? That would be extremely useful.

Let's do it.

There have been other pages of recommended reading on Less Wrong before (and elsewhere), but this post is unique. Here are the rules:

  1. Post the title of your favorite textbook on a given subject.
  2. You must have read at least two other textbooks on that same subject.
  3. You must briefly name the other books you've read on the subject and explain why you think your chosen textbook is superior to them.

Rules #2 and #3 are to protect against recommending a bad book that only seems impressive because it's the only book you've read on the subject. Once, a popular author on Less Wrong recommended Bertrand Russell's A History of Western Philosophy to me, but when I noted that it was more polemical and inaccurate than the other major histories of philosophy, he admitted he hadn't really done much other reading in the field, and only liked the book because it was exciting.

I'll start the list with three of my own recommendations...

 

Subject: History of Western Philosophy

Recommendation: The Great Conversation, 6th edition, by Norman Melchert

Reason: The most popular history of western philosophy is Bertrand Russell's A History of Western Philosophy, which is exciting but also polemical and inaccurate. More accurate but dry and dull is Frederick Copelston's 11-volume A History of Philosophy. Anthony Kenny's recent 4-volume history, collected into one book as A New History of Western Philosophy, is both exciting and accurate, but perhaps too long (1000 pages) and technical for a first read on the history of philosophy. Melchert's textbook, The Great Conversation, is accurate but also the easiest to read, and has the clearest explanations of the important positions and debates, though of course it has its weaknesses (it spends too many pages on ancient Greek mythology but barely mentions Gottlob Frege, the father of analytic philosophy and of the philosophy of language). Melchert's history is also the only one to seriously cover the dominant mode of Anglophone philosophy done today: naturalism (what Melchert calls "physical realism"). Be sure to get the 6th edition, which has major improvements over the 5th edition.

 

Subject: Cognitive Science

Recommendation: Cognitive Science, by Jose Luis Bermudez

Reason: Jose Luis Bermudez's Cognitive Science: An Introduction to the Science of Mind does an excellent job setting the historical and conceptual context for cognitive science, and draws fairly from all the fields involved in this heavily interdisciplinary science. Bermudez does a good job of making himself invisible, and the explanations here are some of the clearest available. In contrast, Paul Thagard's Mind: Introduction to Cognitive Science skips the context and jumps right into a systematic comparison (by explanatory merit) of the leading theories of mental representation: logic, rules, concepts, analogies, images, and neural networks. The book is only 270 pages long, and is also more idiosyncratic than Bermudez's; for example, Thagard refers to the dominant paradigm in cognitive science as the "computational-representational understanding of mind," which as far as I can tell is used only by him and people drawing from his book. In truth, the term refers to a set of competing theories, for example the computational theory and the representational theory. While not the best place to start, Thagard's book is a decent follow-up to Bermudez's text. Better, though, is Kolak et. al.'s Cognitive Science: An Introduction to Mind and Brain. It contains more information than Bermudez's book, but I prefer Bermudez's flow, organization and content selection. Really, though, both Bermudez and Kolak offer excellent introductions to the field, and Thagard offers a more systematic and narrow investigation that is worth reading after Bermudez and Kolak.

 

Subject: Introductory Logic for Philosophy

Recommendation: Meaning and Argument by Ernest Lepore

Reason: For years, the standard textbook on logic was Copi's Introduction to Logic, a comprehensive textbook that has chapters on language, definitions, fallacies, deduction, induction, syllogistic logic, symbolic logic, inference, and probability. It spends too much time on methods that are rarely used today, for example Mill's methods of inductive inference. Amazingly, the chapter on probability does not mention Bayes (as of the 11th edition, anyway). Better is the current standard in classrooms: Patrick Hurley's A Concise Introduction to Logic. It has a table at the front of the book that tells you which sections to read depending on whether you want (1) a traditional logic course, (2) a critical reasoning course, or (3) a course on modern formal logic. The single chapter on induction and probability moves too quickly, but is excellent for its length. Peter Smith's An Introduction to Formal Logic instead focuses tightly on the usual methods used by today's philosophers: propositional logic and predicate logic. My favorite in this less comprehensive mode, however, is Ernest Lepore's Meaning and Argument, because it (a) is highly efficient, and (b) focuses not so much on the manipulation of symbols in a formal system but on the arguably trickier matter of translating English sentences into symbols in a formal system in the first place.

 

I would love to read recommendations from experienced readers on the following subjects: physics, chemistry, biology, psychology, sociology, probability theory, economics, statistics, calculus, decision theory, cognitive biases, artificial intelligence, neuroscience, molecular biochemistry, medicine, epistemology, philosophy of science, meta-ethics, and much more.

Please, post your own recommendations! And, follow the rules.

 

Recommendations so far (that follow the rules; this list updated 02-25-2017):

If there are no recommendations for the subject you want to learn, you can start by checking the Alibris textbooks category for your subject, and sort by 'Top-selling.' But you'll have to do more research than that. Check which textbooks are asked for in the syllabi of classes on your subject at leading universities. Search Google for recommendations and reviews.

Comments (327)

Comment author: michaba03m 16 January 2011 11:24:52AM 4 points [-]

For elementary economics: "Macroeconomics" by Mankiw, is without a doubt the best on the market. It is incredibly well written, and it's so good once you've read the book it fools you into thinking you understand absolutely everything on the topic! "Intermediate Microeconomics" by Varian, is arguably the one to get. It can be a tad dry, and he uses lots of maths. If you don't like the idea of that then "Microeconomics" by Katz and Rosen is a very readable and less mathematical, though not quite as comprehensive as Varian.

Comment author: randallsquared 16 January 2011 04:59:05PM 7 points [-]

it's so good once you've read the book it fools you into thinking you understand absolutely everything on the topic

That's a weird feature to claim for a book you say is both good and only covers elementary knowledge.

Comment deleted 17 January 2011 07:24:24AM [-]
Comment author: wedrifid 17 January 2011 01:25:18PM *  4 points [-]

My dear

There is something about that kind of introduction that makes me reach toward the downvote button. Especially when used in the context of a sentence that does not make grammatical sense and a comment that demonstrates an incorrect understanding of the position being refuted.

"If you must be patronising then at least make sure you're right, for crying out loud!" tends to be my attitude. But maybe that is just me being excessively picky. :)

Comment author: nazgulnarsil 16 January 2011 02:00:37PM 3 points [-]

the absolutely wonderful thing about textbooks is that you can often pick up older editions for the price of a paperback novel.

Comment author: David_Gerard 16 January 2011 03:37:04PM 3 points [-]

Software engineering: everything by Andrew Tanenbaum. The standard texts in the field for good reason.

Comment author: jwhendy 16 January 2011 03:37:14PM *  8 points [-]

Luke -- I wonder if either permalinks to comments answering the task, or direct quotes of them could be added to your main post (say, after two+ weeks have passed)? I know in other posts where a question is asked it can be very difficult to sift through the "meta" comments and the actual answers, especially as comments get into the 100-200+ range!

Comment author: lukeprog 16 January 2011 03:50:51PM 5 points [-]

I was thinking this myself. For example for michaba03m's recommendation below, I could add a line which reads:

  • on economics, michaba03m recommends Mankiw's Macroeconomics over Varian's Intermediate Microeconomics and Katz & Rosen's Macroeconomics.
Comment author: jwhendy 16 January 2011 03:52:34PM 1 point [-]

Love it -- I also wondered if you might be planning something like this... figured it didn't hurt to suggest it anyway, though!

Comment author: michaba03m 17 January 2011 08:22:50PM 1 point [-]

Sorry Luke I rushed that a little bit and didn't check before hitting 'comment'. In economics I would say you should read macroeconomics and microeconomics separately, and most college-level textbooks are on either one rather than both anyway. So Mankiw is definitely the best on Macro, whilst Varian is the best for Micro, but his is quite dry and mathsy, whereas for a Micro alternative Katz and Rosen is more readable but less mathematical.

So for Macro, go for Mankiw, and for Micro go Katz and Rosen if you can't handle Varian.

Hope that clears that up!

Comment author: gwern 16 January 2011 05:14:02PM *  12 points [-]

I can't help but question this post.

Textbook recommendations are all over. From the old SIAI reading shelf to books individually recommended in articles and threads to wiki pages to here (is this even the first article to try to compile a reading list? I don't think it is.)

Maybe we would be better off adding pages to the LW wiki. So for [[Economics]] a brief description why economics is important to know, links to relevant LW posts, and then a section == Recommended reading ==. And so on for all the other subjects here.

Work smarter, not harder!

Comment author: lukeprog 16 January 2011 05:31:21PM *  21 points [-]

The problem is that lots of textbook recommendations are not very good. I've been recommended lots of bad books in my life. That's what is unique about this post: it demands that recommendations be given only by people who are fairly well-read on the subject (at least 3 textbooks).

But yes, adding this data to the Wiki would be great.

Comment author: nazgulnarsil 16 January 2011 05:39:56PM 7 points [-]

agreed, but the idea to add this info to the wiki once the thread has matured is a good one.

Comment author: Will_Sawin 16 January 2011 05:51:08PM 3 points [-]

However, a centralized repository-of-textbooks is also a good idea.

Comment author: XiXiDu 16 January 2011 05:53:59PM 9 points [-]

Textbook recommendations are all over.

Since the parent omitted a link: singinst.org/reading/

Comment author: rwallace 16 January 2011 05:25:26PM 10 points [-]

General programming: Structure and Interpretation of Computer Programs. Focuses on the essence of the subject with such clarity that a novice can understand the first chapter, yet an expert will have learned something by the last chapter.

Specific programming languages: The C Programming Language, The C++ Programming Language, CLR via C#. Informative to a degree that rarely coexists with such clarity and readability.

AI: Artificial Intelligence: a Modern Approach. Perhaps the rarest virtue of this work is that not only does it give about as comprehensive a survey of the field as will fit in a single book, but casts a cool eye on the limitations as well as strengths of each technique discussed.

Compiler design: Compilers: Principles, Techniques and Tools. The standard textbook for good reason.

Comment author: lukeprog 16 January 2011 05:35:07PM 3 points [-]

rwallace,

Thanks for your recommendations! Your comment made me realize I was not specific enough in my list of rules, so I modified the third rule to the following:

"You must briefly name the other books you've read on the subject and explain why you think your chosen textbook is superior to them."

Would you please do us the favor of naming the other books you've read on these subjects, and why your recommendations are superior to them? That would be much appreciated.

Comment author: rwallace 16 January 2011 05:44:50PM 1 point [-]

A problem is that in many cases it was long enough ago (e.g. I got into C programming in the 1980s, C++ around 1990) that I don't remember the names of the other books I read. The ones that stuck in my mind were the memorably good ones. (Memorably bad things can do likewise of course, but few textbooks fall into that category -- the point of this post after all is that textbooks tend to have higher standards than most media.)

Comment author: [deleted] 16 January 2011 05:41:43PM 4 points [-]

Is "The C Programming Language" Kernighan & Ritchie? (titles are often very generic so it's nice to see authors as well.)

Comment author: rwallace 16 January 2011 05:46:23PM 1 point [-]

Yes.

Comment author: barrkel 17 January 2011 12:33:53PM 9 points [-]

I don't agree on the dragon book (Compilers: Principles, Techniques and Tools). It focuses too much on theory of parsing for front end stuff, and doesn't really have enough space to give a good treatment on the back end. It's a book I'd recommend if you were writing another compiler-compiler like yacc.

I'd rather suggest Modern Compiler Implementation in ML; even though there are C and Java versions too, a functional language with pattern matching makes writing a compiler a much more pleasant experience.

(I work on a commercial compiler for a living.)

Comment author: [deleted] 16 January 2011 05:30:02PM *  19 points [-]

Subject: Representation Theory

Recommendation: Group Theory and Physics by Shlomo Sternberg.

This is a remarkable book pedagogically. It is the most extremely, ridiculously concrete introduction to representation theory I've ever seen. To understand representations of finite groups you literally start with crystal structures. To understand vector bundles you think about vibrating molecules. When it's time to work out the details, you literally work out the details, concretely, by making character tables and so on. It's unique, so far as I've read, among math textbooks on any subject whatsoever, in its shameless willingness to draw pictures, offer physical motivation, and give examples with (gasp) literal numbers.

Math for dummies? Well, actually, it is rigorous, just not as general as it could potentially be. Also, many people's optimal learning style is quite concrete; I believe your first experience with a subject should be example-based, to fix ideas. After all, when you were a kid you played around with numbers long before you defined the integers. There's something to the old Dewey idea of "learning by doing." And I have only seen it tried once in advanced mathematics.

Fulton and Harris won't do this. The representation theory section in Lang's Algebra won't do this -- it starts about three levels of abstraction up and stays there. Weyl's classic The Theory of Groups and Quantum Mechanics isn't actually the best way to learn -- the group theory and the physics are in separate sections and both are a little compressed and archaic in terminology. Sternberg is really a different thing entirely: it's almost more like having a teacher than reading a textbook.

The treatment is really most relevant for physicists, but even if you're not a physicist (and I'm not), if you have general interest in math, and background up to a college abstract algebra course, you should check this out just to see what unusually clear, intuitive mathematical writing looks like. It will make you happy.

Comment author: lukeprog 16 January 2011 05:53:27PM 1 point [-]

Thanks for all the detail! I've added it to the list above.

Comment author: komponisto 17 January 2011 06:45:59PM 2 points [-]

Also, many people's optimal learning style is quite concrete; .

I hasten to point out (well, actually I didn't hasten, I waited a day or two, but...) that while this is true for many people, it isn't true for all, and, in particular, it isn't true for me. (See here.)

I believe your first experience with a subject should be example-based, to fix ideas. After all, when you were a kid you played around with numbers long before you defined the integers

I don't think the way I learned mathematics as a young child (or indeed in school at any time, up to and including graduate school) was anywhere near optimal for the way my mind works.

The best way for me would have been to work through Bourbaki, chapter by chapter, book by book, in order. I'm dead serious. (If I were making an edition for my young self I would include plenty of colorful but abstract pictures/diagrams.)

Comment author: [deleted] 17 January 2011 07:38:43PM 2 points [-]

I assumed there were some folks like you but I'd never met one. Shame on me for making too many assumptions.

Comment author: komponisto 17 January 2011 11:02:05PM 5 points [-]

I assumed there were some folks like you but I'd never met one

It's not as stark as that. For example, Alicorn, whom I believe you've met, shares with me a psychological need for concepts to be presented in logical order.

In my case, if you're curious, I think the reason I'm the way I am comes down to efficient memory. To remember something reliably I have to be able to mentally connect it to something I already know, and ultimately to something inherently simple. The reason I can't stand ad-hoc presentations of mathematics is that remembering their contents (let alone being able to apply those contents to solve problems) is extremely cognitively burdensome. It requires me to create a new mental directory when I would prefer to file new material as a subdirectory under an existing directory. (I don't mind having lots of nested layers, but strongly prefer to minimize the number of directories at any given level; I like to expand my tree vertically rather than horizontally.)

This explains why it took me forever to learn the meaning of "k-algebra". The reason was that (for a long time) every time I encountered the term, the definition was always being presented in passing, on the way to explaining something else (usually some problem in algebraic geometry, no doubt), instead of being included among The Pantheon Of Algebraic Structures: Groups, Rings, Fields etc. -- so my brain didn't know where to store it.

Comment author: steven0461 17 January 2011 11:51:33PM 2 points [-]

I find it takes much more effort to learn things when different sources don't coordinate well on definitions, notation, and the material's hierarchical structure. For example, if everyone agreed on how to present the Nine Great Laws of Information Theory, that would make them much easier for me to remember them. It's as if, instead of learning the overlap between different presentations, my brain shuts down and doesn't trust any of them. But it's hard to settle on such cognitive coordination equilibria.

Comment author: SilasBarta 18 January 2011 12:31:13AM *  2 points [-]

In my case, if you're curious, I think the reason I'm the way I am comes down to efficient memory. To remember something reliably I have to be able to mentally connect it to something I already know, and ultimately to something inherently simple.

Interesting. That sounds like my habit of making sure everything I learn plugs into my model for everything else, and how I'm bothered if it doesn't (literature and history class, I'm looking in your general direction here). Likewise, how I don't regard myself as understanding a subject until my model is working and plugged in (level 2 in my article).

This is why I've usually found it easy to explain "difficult" topics to people, at least in person: per my comment here, I just find the inferentially-nearest thing we both understand, and build out stepwise from there. And, in turn, why I'm bothered by those who can't likewise explain -- after all, what insights are they missing by having such a comparmentalized (level 1) understanding of the topic?

Comment author: [deleted] 18 January 2011 12:58:43AM 2 points [-]

Well, I can see the need to have the concepts fit together. What I need on a first pass through a subject is something that can attach to the pre-abstract part of my brain. A picture, even a "real-world example." Something to keep in mind while I later fill in the structure.

The way I see it (which I realize is more of a metaphor than an explanation) human brains evolved to help us operate in large social groups of other primates. We're very good at understanding stories, socialization, human faces, sex and politics. I think for a lot of people (myself included) the farther we get from that core, the more help we need understanding concepts. I need to make concessions to human frailty by adding pictures and applications, if I want to learn as well as possible. (This is something that people in abstract fields rarely admit but I think LessWrong is a good place to be frank.)

Comment author: realitygrill 17 January 2011 09:34:06PM 2 points [-]

Have you ever read Group Theory and Its Applications in Physics by Inui, Tanabe, Onodera? I have never been able to find this book and it's been recommended to me several times as the pedagogically best math/physics book they've ever read.

Comment author: Douglas_Knight 17 January 2011 09:38:56PM 3 points [-]

Fulton and Harris won't do this.

Won't do what? Almost everything you say about Sternberg seems to me to apply to Fulton & Harris. I have not looked at Sternberg, and it may well be better in all these ways, but your binary dismissal of F&H seems odd to me.

Comment author: sark 16 January 2011 06:53:24PM *  1 point [-]

But what exactly do you want to learn? If you study widely, surely you are trying to learn something different from what specialists in their respective fields try to learn. They might for example forgo a general understanding for specialist knowledge, because that is how they could best hope to contribute something unique to their field and hence reap the rewards of status. They might overemphasize certain methods of their fields since only discoveries through the use of such methods can hope to contribute results to their field.

An example:

the introductory course is increasingly tailored not for the majority of students for whom it will be their only economics course, but for the negligible fraction who will go on to become professional economists. Such courses focus on the mathematical models that have become the cornerstone of modern economic theory. These models prove daunting for many students and leave them little time and energy to focus on how basic economic principles help explain everyday behavior.

from here

Perhaps it's better to have textbooks written for other academics outside of a specialty, since such textbooks are forced to be tolerable/comprehensible to outsiders they are less susceptible to disciplinary navel gazing. They might aim to show off their specialty to others, instead of showing off the author's prowess within the specialty, but even this is an improvement, since they must achieve that through appealing to a wider audience with diverse interests/aptitudes.

What would be a general solution? Michael Vassar's idea of 'lightness of curiosity' helps I think. You should always make sure your curiosity tracks your goals. Do not rely on Schmidhuber's notion of curiosity as compression, because a discipline can hoodwink you by introducing difficult and enticing subproblems within the field which only practitioners would be interested in solving.

Comment author: lukeprog 16 January 2011 07:29:58PM 2 points [-]

sark,

Yes, that's something I learned only recently. My earlier studies touched on all kinds of subjects, without a clear focus on where I was going or why I needed to spend time thinking about certain problems. These days, my study is tightly focused on the subjects that interest me, with the additional burden of occasionally reading philosophy of religion as well so that I can keep things interesting at my blog 'Common Sense Atheism.'

Comment author: Vaniver 17 January 2011 05:31:19AM 3 points [-]

Yes, that's something I learned only recently. My earlier studies touched on all kinds of subjects, without a clear focus on where I was going or why I needed to spend time thinking about certain problems.

It seems to me that some sort of rudderless exploration is necessary to get a large enough set of potential problems for you to select a good one to focus on. After all, outside of very limited contexts you can't say "best possible," just "best I've seen."

Comment author: nykos 17 January 2011 05:42:12PM 5 points [-]

I think that it pays to be rationally ignorant. It is an economic fact that the more people specialize, the more they get paid and the chance of making a significant contribution in their particular field increases. You can't achieve your best in being a doctor if you spend valuable time reading textbooks about Western philosophy or quantum computing instead of reading textbooks about diseases. There is a saying capturing this thought: "jack of all trades and master of none". Sure, there are some fields such as AI at the intersection of many sciences - however, I doubt that most people on this blog (including me) are capable of handling that much information while producing new results in the field in a reasonable amount of time.

So, instead of reading the intro textbook of each field/science (I bet there are more such fields than anyone can handle in a normal, no-singularity lifespan), the best approach for me is to learn a little about each field in my free time - just enough so that I will not be ignorant to the point of making serious mistakes about the nature of reality, and sufficiently easy on the mind so that I maintain the processing power for the main work: digging as deep as possible into the field of my choice.

So, I disagree with the author and think that Teaching Company courses are more useful than textbooks... except for the textbooks pertaining to your chosen specialty.

There is a real danger in becoming more absorbed with the exploration of rationality and science than with focusing on, and excelling in, your own field. I myself am guilty of this.

Comment author: Kaj_Sotala 18 January 2011 08:36:24AM 4 points [-]

I have a gut feeling that there are lots of low-hanging fruit that could be picked by people reading more widely and applying the tools of one discipline into another. For instance, Aubrey de Grey claims that because he had a computer science background, he was able to start contributing new content to biology after studying for the field for only a very short time. There might be simple, obvious ways of expanding a field by bringing in new tools of analysis from another field, but none of this happens because most people only specialize in their own field.

I'm also reminded of this discussion:

But some years back, reading an interesting article by Akerlof and Yellin on why changes that should have reduced the number of children born to unmarried mothers had been accompanied instead by a sharp increase, I was struck by the fact that they had used game theory to make an argument that could have been presented equally well, perhaps more clearly, with supply and demand curves. Their analysis was simply an application of the theory of joint products—sexual pleasure and babies in a world without reliable contraception or readily available abortion. Add in those technologies, making the products no longer joint, and the outcome changes, making some women who want babies unable to find husbands to help support them.

Assume, for the moment, that I am right, that both economics in the journals and economics in the classroom emphasize mathematics well past the point where it no longer contributes much to the economics. Why?

The answer, I suspect, takes us back to Ricardo's distinction between the intensive and extensive margins of cultivation. Expanding production on the intensive margin means getting more grain out of land already cultivated, expanding it on the extensive margin means getting more grain by bringing new land into cultivation.

In economics, the intensive margin means writing new articles on subjects that smart people have been writing articles about for most of the past century—new enough, at least, to get published. One way of doing it, assuming you don't have some new and interesting economic idea, is to apply a new tool, some recently developed mathematical approach,. It has not been done before, that tool not having existed before, so with luck you can get published.

The extensive margin is the application of the existing tools of economics, and mathematics where needed, to new subjects. Examples include public choice theory, law and economics, and, somewhat more recently, behavioral economics. The same thing can be done on a smaller scale if you happen to think of something new that is relevant to more conventional topics. I have considerable disagreements with Robert Frank, some exposed in exchanges between us on this blog a while back. But when, in Choosing the Right Pond, he showed how the fact that relative as well as absolute outcomes matter to people could be incorporated into conventional price theory, he really was working new ground and, in the process, teaching the rest of us something interesting.

My conclusion is that, if you want to do interesting economics, your best bet is probably to work on the extensive margin—better yet, if sufficiently clever and lucky, to extend it.

Working on the intensive margin seems to me to be what happens if you specialize too deeply in just one field or two (economics and math in this example), while work on the extensive margin requires you to read widely or otherwise become familiar of new areas to which your standard tools to be applied to.

Comment author: PeterisP 18 January 2011 11:25:27PM 1 point [-]

The saying actually goes 'jack of all trades and a master of none, though oft better than a master of one'.

There are quite a few insights and improvements that are obvious with cross-domain expertise, and much of the new developments nowadays pretty much are merging of two or more knowledge domains - bioinformatics as a single, but not nearly only example. Computational linguistics, for example - there are quite a few treatises on semantics written by linguists that would be insightful and new for computer science guys handling also non-linguistic knowledge/semantics projects.

Comment author: Tiiba 16 January 2011 07:09:07PM 2 points [-]

In college, I found most of the time that the professor's lecture notes contain almost everything of value that both the textbook and the lecture contains, but they contain ten times less text. This led me to believe that textbooks are a terribly inefficient way to convey facts, by comparison to the format of lecture notes. Books are words, words, words, flowery metaphors, digressions, etc. Hell, I don't know what they spend all those words on. But I know that, potentially, lecture notes are one fact after another.

Comment author: lukeprog 16 January 2011 07:26:40PM 8 points [-]

I find all those extra words surrounding the bare facts in textbooks to be highly useful. That's what helps me not just memorize the teacher's password but really understand the material at a gut level.

Comment author: Tiiba 16 January 2011 08:11:28PM 0 points [-]

They get ME bored. Every book is six hundred to a thousand pages, and when you're done with it, you've got a hundred pages worth of knowledge. I think it's better to memorize some passwords, then separately look up specific ideas that didn't make sense.

Comment author: lukeprog 16 January 2011 08:13:59PM 1 point [-]

Fair enough. :)

I love reading a good textbook. Good nonfiction is so much more exciting for me than good fiction. And of course, I learn far more from good nonfiction.

Comment author: NihilCredo 17 January 2011 11:27:55AM 2 points [-]

I usually find that (good) textbooks can let you learn the subject matter by yourself, whereas lecture notes are excellent reference material but, if you didn't attend the lectures, they're just not going to make for good building material on their own.

Comment author: prase 17 January 2011 06:07:27PM 1 point [-]

I join NihilCredo and lukeprog in this. Textbooks usually have less text than what I would find ideal, not more. Lecture notes (and many textbooks which seemingly obey the even formula to text ratio) take me more time to read than a book which contains the same number of formulas and four times as much text. I can't continue reading after having stumbled upon something which looks like an inconsistency, non-sequitur or counterintuitive definition (that usually first happens on page 5 or so) and then have to spend time trying to find out what is wrong (and if I fail, then must spend some more time persuading myself that it doesn't matter and reading can continue). On the other hand, if the author spends some time and pages explaining, such events occur much less frequently.

Comment author: Tiiba 17 January 2011 06:54:52PM 0 points [-]

You guys do what works for you, and I'll do what works for me. Maybe I just don't have the patience. Or maybe you don't have something required to understand lossily compressed info. Or both. I just know that books take all day long and help as much as short online tutorials. And the tutorials are often free.

Comment author: tel 18 January 2011 04:11:53PM 0 points [-]

If lecture notes contain as much relevant information as a book, then you should be able to, given a set of notes, write a terse but comprehensible textbook. If you're genuinely able to get that much out of notes, then yes that definitely works for you.

The concern is instead if reading a textbook only conveys a sparse, unconvincing, and context-free set of notes (which is my general impression of most lecture notes I've seen).

Both depend heavily on the quality of notes, textbook, subject, and the learning style you use, but I think it's a lot of people's experience that lecture notes alone convey only a cursory understanding of a topic. Practically enough sometimes, test-taking enough surely, but never too many steps toward mastery.

Comment author: PhilGoetz 23 January 2011 08:22:27PM 2 points [-]

How about you start a thread for recommending online tutorials?

Comment author: Cyan 16 January 2011 07:31:16PM *  7 points [-]

In Bayesian statistics, Gelman's Bayesian Data Analysis, 2nd ed (I hear a third edition is coming soon) instead of Jaynes's Probability Theory: The Logic of Science (but do read the first two chapters of Jaynes) and Bernardo's Bayesian Theory.

Comment author: lukeprog 16 January 2011 07:40:01PM 1 point [-]

Cyan,

Could you give us some reasons?

Comment author: Cyan 16 January 2011 07:51:19PM 5 points [-]

Both Jaynes's and Bernardo's texts have a lot of material on why one ought to do Bayesian statistics; Gelman text excels in showing how to do it.

Comment author: lukeprog 16 January 2011 08:10:58PM 0 points [-]

Thanks. I added this to the list.

Comment author: tel 18 January 2011 03:33:07PM *  1 point [-]

Gelman's text is very specifically targeted at the kinds of problems he enjoys in sociology and politics, though. If you're interested in solving problems in that field or like it (highly complex unobservable mechanisms, large number of potential causes and covariates, sensible multiple groupings of observations, etc) then his book is great. If you're looking at problems more like in physics, then it won't help you at all and you're better off reading Jaynes'.

(Also recommended over Gelman's Applied Regression and Modeling if the above condition holds.)

Comment author: Cyan 19 January 2011 01:17:39AM *  1 point [-]

Ah, interesting. I used the material I learned from that book in my thesis on data analysis for proteomics, so you can expand the list of topics to include biological data too; biology problems tend to fit your list of problem characteristics.

Comment author: Zetetic 13 May 2011 11:38:34PM 0 points [-]

highly complex unobservable mechanisms, large number of potential causes and covariates, sensible multiple groupings of observations, etc

Hmm, I might be totally off base here, but wouldn't that sort of thing be useful for reasoning about highly powerful optimization processes that would be driven to maximize their expected utility by figuring out what actions would decrease the entropy of a desirable portion of state space by working from massive amounts of input data? Maybe I should check it out either way.

Comment author: tel 31 May 2011 04:54:10AM 2 points [-]

I'm sorry, as I'm reading it that sounds rather vague. Gelman's work stems largely from the fact that there is no central theory of political action. Group behavior is some kind of sum of individual behaviors, but with only aggregate measurements you cannot discern the individual causes. This leads to a tendency to never see zero effect sizes, for instance.

Comment author: Jonathan_Graehl 17 January 2011 04:27:19AM *  7 points [-]

Subjects: algorithms/computational complexity, physics, Bayesian probability, programming

Introduction to Algorithms (Cormen, Rivest) is good enough that I read it completely in college. The exercises are nice (they're reasonably challenging and build up to useful little results I've recalled over my programming career). I think it's fine for self-study; I prefer it to the undergrad intro level or language-specific books. Obviously the interesting part about an algorithm is not the Java/Python/whatever language rendering of it. I also prefer it to Knuth's tomes (which I gave up on finishing - not enough fun). Knuth invents problems so he can solve them. He explains too much minutia. But his exercises are varied and difficult. If you like very hard puzzles, it's a good place to look.

Introduction to Automata Theory, Languages, and Computation (Hopcroft+Ullman) was also good enough for me to read. I've referred to it many times since. However, it's apparently not well-liked by others; maybe because it's too dense for them? I haven't read any other textbooks in the area.

The Feynman Lectures on Physics are also fun to read. But I doubt someone could use them as an intro course on their own. Because they're filled with entertaining tidbits, I was tempted to read through them without actually following the math 100%. Obviously this somewhat defeats the purpose. That's always a danger with well written technical material consumed for pleasure. I had already taken a few physics courses before I read Feynman; his lectures were better than the course textbooks (which I already forgot).

I didn't care for Jaynes. I only read about 700 pages, though. I remember there was some group reading effort that stopped showing up on LW after just a few chapters :)

For plain old programming, I've read quite a few books, and really liked The Practice of Programming - it was too short. I read Dijkstra's a discipline of programming and loved it for its idea to define program semantics precisely and to prove your code correct (nobody really practices this; it's too slow and hard compared to "debugging"), but it's probably not worth the price - I checked it out from a library.

I also agree with rwallace's recommendations also, except that the AI text is not especially useful (not that I know of a better one). I would not give SICP to a novice, though. Although I had done everything described in the book before (and already knew lisp), it did increase my appreciation of using closures and higher order functions as an alternative for the usual imperative/OO stuff. It also covers interpretation and compilation quite well (skipping the character-sequence parsing part - this is lisp, after all).

Comment author: lukeprog 17 January 2011 04:55:33AM 1 point [-]

Jonathan_Graehl,

Thanks for your recommendations, though I've set a rule that I won't add recommendations to the list in the original post unless those recommendations conform to the rules. Would you mind adding to what you've written above so as to conform to rule #3?

For example, you could list two other books on algorithms and explain why you prefer Introduction to Algorithms to those other books. And you could do the same for the subject of physics, and the subject of programming, and so on.

Comment author: gjm 18 January 2011 01:58:56AM 5 points [-]

Well, let me do Jonathan's job for him on one of those.

Introduction to Algorithms by Cormen, Leiserson, Rivest, and (as of the second edition) Stein is a first-rate single-volume algorithms text, covering a good selection of topics and providing nice clean pseudocode for most of what they do. The explanations are clear and concise. (Readers whose tolerance for mathematics is low may want to look elsewhere, though.)

Two obvious comparisons: Knuth's TAOCP is wonderful but: very, very long; now rather outdated in the range of algorithms it covers; describes algorithms with wordy descriptions, flowcharts, and assembly language for a computer of Knuth's own invention. When you need Knuth, you really need Knuth, but mostly you don't. Sedgwick's Algorithms (warning: it's many years since I read this, and recent editions may be different) is shallower, less clearly written, and frankly never gave me the same the-author-is-really-smart feeling that CLRS does.

(If you're going to get two algorithms books rather than one, a good complement to CLRS might be Skiena's "The algorithm design manual", more comments on which you can find on my website.)

Comment author: Jonathan_Graehl 26 January 2011 02:38:33AM 2 points [-]

Thanks. I really didn't have the ability to easily recall names of what few alternatives I've read (although in the area of programming in general, there are dozens of highly recommended books I've actually read - Design Patterns (ok), Pragmatic Programmer (ok), Code Complete (ok), Large Scale C++ Software Design (ok), Analysis Patterns (horrible), Software Engineering with Java (textbook, useless), Writing Solid Code (ok), object-oriented software construction (ok, sells the idea of design-by-contract), and I could continue listing 20 books, but what's the point. These are hardly textbooks anyway.

On algorithms, other than Knuth (after my disrecommendation of his work, I just bought his latest, "Combinatorial Algorithms, part 1"), really the only other one I read is "Data Structures in C" or some similar lower level textbook, which was unobjectionable but did not have the same quality.

Comment author: gjm 26 January 2011 04:09:41PM 0 points [-]

You're welcome! (Of the other books you mention that I've read, I agree with your assessment except that I'd want to subdivide the "ok" category a bit.)

Comment author: Davidmanheim 18 January 2011 03:38:52PM 0 points [-]

As a counterpoint to Hopcroft+Ullman, from another who has not read other books, Problem Solving in Automata, Languages, and Complexity by Ding-Zhu Du and Ker-I Ko was terrific. I did it as an undergraduate independent study class, completely from this book, and found it to be easy to follow if you are willing to work through problems.

Maybe we need someone who knows something more on the subject?

Comment author: Jonathan_Graehl 26 January 2011 02:47:37AM 0 points [-]

Hopcroft+Ullman is very proof oriented. Sometimes the proof is constructive (by giving an algorithm and proving its correctness). I liked it. There may be much better available for self-study.

Specialty algorithms: I briefly referenced Numerical Optimization and it seems better than Numerical Recipes in C. I didn't read it cover to cover.

Algorithms on Strings, Trees, and Sequences (Gusfield) was definitely a good source for computational biology algorithms (I don't do computation biology, but it explains fairly well things like suffix trees and their applications, and algorithms matching a set of patterns against substrings of running text).

Foundations of Natural Language Processing is solid. I don't think there's a better textbook (for the types of dumb, statistics/machine-learning based, analysis of human speech/text that are widely practiced). It's better than "Natural Language Understanding" (Allen), which is more old-school-AI.

Comment author: lunchbox 17 January 2011 04:41:05AM 7 points [-]

Here is a very similar post on Ask Metafilter. (It is actually Ask Metafilter's most favorited post of all time.)

Comment author: lukeprog 17 January 2011 04:56:28AM 2 points [-]

Ah, yes, that list is one of my favorites. But, it doesn't enforce anything like the rules I've given above, which I think are useful.

Comment author: James_Miller 17 January 2011 08:39:42AM *  4 points [-]

Subject: Microeconomics

Recommendation: My Textbook

Obviously I have some massive bias issues in evaluating my own book, but the kind of person who regularly reads and contributes to LessWrong is probably the kind of person who would write a textbook LessWrongers might want to read. Plus, a used copy costs only $3 at Amazon.

My book even briefly discusses the singularity.

Mankiw's Principles of Microeconomics and Heyne's The Economic Way of Thinking are also good.

Comment author: orthonormal 17 January 2011 06:39:11PM 4 points [-]

I'm glad you mentioned that you've written a textbook, but I'd discount your recommendation for obvious reasons. Has anyone else read Miller's Principles of Microeconomics?

Comment author: InquilineKea 17 January 2011 10:38:44AM *  5 points [-]

It really depends on your learning style, and whether you learn best through examples=>generalizations or generalizations=>examples.

Similarly, some people may learn faster from a non-rigorous approach (and fill in the gaps later), while others may learn faster from a more rigorous approach. Some people might stare at a text for hours, but might be able to motivate themselves to learn the material much faster if they had some concrete examples first (using the Internet as a supplementary resource can help in that). I actually find it easier to learn molecular cell biology through Wikipedia articles than through textbooks, because Wikipedia articles often contain more of the information that's more emotionally significant to many people (even if not epistemically significant).

For example, I really do feel that I would have learned physics and math much faster if I learned them through computer simulations (proofs could be done later - I tend to just stare at proofs if they're presented first). I'm an inductive learner, not a deductive learner, and I tend to stare at texts that are overly deductive (part of it owes to my severe inattentive ADD, but maybe some non-ADDers are in the same boat as I am there)

In general, I find lectures extremely inefficient, unless there is space for significant amounts of one-to-one feedback, either through insanely small classes or a teacher who allows you to be their pet. Since these rarely happen in college, I generally find learning from textbooks more efficient. Podcasts/video lectures are often VERY inefficient ways to learn since you can read MUCH faster than you can listen, and it's much more of a hassle to repeat a part you don't quite understand.

Here's a quote I really like:

"Similarly, no one has been able to confirm any certain limits to the speed with which man can learn. Schools and universities have usually been organized as if to suggest that all students learn at about the same rather plodding and regular speed. But, whenever the actual rates at which different people learn have been tested, nothing has been found to justify such an organization. Not only do individuals learn at vastly different speeds and in different ways, but man seems capable of astonishing feats of rapid learning when the attendant circumstances are favorable. It seems that, in customary educational settings, one habitually uses only a tiny fraction of one's learning capacities." Encyclopedia Britannica, Philosophy of Education

====

That being said, here's a list of books I wish I had studied from instead of the standard textbooks: http://www.amazon.com/gp/richpub/syltguides/fullview/R2BKS9X5I8D9Y/ref=cm_sylt_byauthor_title_full_1

Also, Razib Khan has collected some pretty amazing books (you can find them on http://www.gnxp.com).

Comment author: Hurt 17 January 2011 01:23:47PM 8 points [-]

While the following isn't really a textbook, I highly recommend it for helping you to improve your skill as a reader. "How to Read a Book" by Mortimer Adler and Charles Van Doren. It covers a variety of different techniques from how to analytically take apart a book to inspectional techniques for getting a quick overview of a book.

I never knew how to read analytically, I had never been taught any techniques for actually learning from a book. I always just assumed you read through it passively.

http://www.amazon.com/How-Read-Book-Touchstone-book/dp/0671212095

Comment author: jsalvatier 17 January 2011 04:14:39PM 1 point [-]

It looks interesting, but I am surprised it's 400 pages long, is there really that much in the way of reading strategies?

Comment author: Hurt 17 January 2011 11:07:36PM 5 points [-]

It has a fairly large appendix (~70 pgs) of recommended reading and sample tests/examples at the end of the book. It also has several sections on reading subject specific matter i.e. How to read History, Philosophy, Science, Practical books, etc. It also covers agreeing or disagreeing with an author, fairly criticizing a book, aids to reading. I think reading strategies may have been too narrow a choice of words. It really covers the "Art of Reading". A good set of English classes would probably cover similar ground, although I didn't see anything like this in my high school or undergraduate education.

Comment author: [deleted] 27 January 2011 06:31:21PM 0 points [-]

Second the vote for this book, though there is quite a bit of fluff (most of the chapters on strategies for readings specific topics I found less than useful) - it really does a great job of explaining how to extract information from a book.

The key insight I took away was that a book isn't just a long string of words broken up into various sections - a book is a little machine that produces an argument, and to really understand that argument you need to figure out what the machine is doing.

Comment author: jsalvatier 17 January 2011 04:01:51PM *  17 points [-]

Update see my comment for new thoughts

Topic: Introductory Bayesian Statistics (as distinct from more advanced Bayesian statistics)

Recommendation: Data Analysis: A Bayesian Tutorial by Skilling and Sivia

Why: Sivia's book is well suited for smart people who have not had little or no statistical training. It starts from the basics and covers a lot of important ground. I think it takes the right approach, first doing some simple examples where analytical solutions are available or it is feasible to integrate naively and numerically. Then it teaches into maximum likelihood estimation (MLE), how to do it and why it makes sense from a Bayesian perspective. I think MLE is a very very useful technique, especially so for engineers. I would overall recommend just Part I: The Essentials, I don't think the second half is so useful, except perhaps the MLE extensions chapter. There are better places to learn about MCMC approximation.

Why not other books?

Bayesian Data Analysis by Gelman - Geared more for people who have done statistics before.

Bayesian Statistics by Bolstad - Doesn't cover as much as Sivia's book, most notably doesn't cover MLE. Goes kinda slowly and spends a lot of time on comparing Bayesian statistics to Frequentist statistics.

The Bayesian Choice - more of a mathematical statistics book, not suited for beginners.

Comment author: lukeprog 17 January 2011 07:34:35PM 1 point [-]

Nice!

Comment author: jsalvatier 20 September 2011 04:13:32PM *  8 points [-]

Brandon Reinhart used both Sivia's book and Bolstad's book and found (3rd message) Bolstad's book better for those with no stats experience:

For statistics, I recommend An Introduction to Bayesian Statistics by William Bolstad. This is superior to the "Data Analysis" book if you're learning stats from scratch. Both "Data Analysis" and "Bayesian Data Analysis" assume a certain base level of familiarity with the material. The Bolstad book will bootstrap you from almost no familiarity with stats through fairly clear explanations and good supporting exercises.

Nonetheless, it's something you should do with other people. You may not notice what you aren't completely comprehending otherwise. Do the exercises!

Based on these comments, I think I was underestimating inferential distance, and I now change my recommendation. You should read Bolstad's book first (skipping the parts comparing bayesian and frequentist methods unless that's important to you) and then read Sivia's book. If you have experience with statistics you may start with Sivia's book.

Comment author: beoShaffer 05 November 2011 04:29:46AM 0 points [-]

Is Gleman's book a good recommendation for people who have done frequentist statistics and/or combinatorics? I have free access to it and basic familiarity with both.

Comment author: jsalvatier 17 January 2011 04:27:01PM 5 points [-]

Since many people will be buying books here, this is a good place to recommend that people use a book-price search engine to find the best possible price on a book. I have found the best one to be BooksPrice. DealOz is also decent. I am not affiliated with either of these in any way.

Comment author: anonym 20 January 2011 05:39:34AM 1 point [-]

There are also price alert services that will email you when a book reaches a certain price. I've found this really useful, because while the latest version of a textbook might be $100 new and $60 used, you can sometimes get the same version used in great condition for much lower than the normal used price, especially after the end of a semester.

This is really useful when you don't need the book soon but know that you'd like to buy it at some point.

Comment deleted 17 January 2011 04:28:14PM *  [-]
Comment author: jsalvatier 17 January 2011 04:55:59PM *  0 points [-]

I haven't studied real analysis, could you explain what advantages the guage integral is better than the lebesgue integral? Edit: maybe just respond to SarahC.

Comment author: [deleted] 17 January 2011 05:04:38PM *  6 points [-]

Hmm. Upvoted for contributing to a good topic but I'm not sure I agree.

I just looked up the gauge integral because I wasn't familiar with it. For those curious about the debate, here's the introduction to the gauge integral I found, which has a lot of relevant information. My beef with this is precisely that it doesn't use the general background of measure theory (sigma-algebras, measurable functions, etc.) and you're going to need that background to do useful things. The gauge integral approach doesn't give you the tools to generalize to scenarios like Brownian motion where you need to construct different measures; also, the gauge integral doesn't come with a lot of nice convergence theorems the way the Lebesgue measure does.

I don't find the standard treatment of measure theory especially hard; it takes about a month to understand everything up to the Lebesgue integral, which isn't an obscene time commitment.

Also, there's some virtue to just being familiar with the definitions and concepts that everybody else is. (It's not just mathematicians "refusing to update." I know for sure that economists, and potentially people in other fields, speak the language of standard measure theory. But maybe it's not everyone. What are you using measure theory for?)

If you're looking for an easier, more straightforward treatment than Rudin, I'd recommend Cohn's Measure Theory. I'm not sure why, but it feels friendlier and less digressive.

Comment deleted 18 January 2011 06:14:40AM [-]
Comment author: komponisto 18 January 2011 07:50:54AM 1 point [-]

I also rank Halmos higher than Cohn in terms of measure theory books

Halmos, by the way, is a top-notch mathematical author in general. Every one of his books is excellent. Finite-Dimensional Vector Spaces in particular is a classic.

Comment author: rich 18 January 2011 12:06:22PM 0 points [-]

I think that's the only book I kept from my Maths degree. In hardback, too. I have lent it to a colleague and keep a careful eye on where it is every couple of weeks...

Comment author: JoshuaZ 17 January 2011 05:12:14PM 0 points [-]

I'm not sure why you consider the gauge integral to be easier to understand the Lebesgue integral. It may be due to learning Lebesgue first, but I find it much more intuitive.

Also:

Royden is slightly better in this respect. The first four chapters are excellent, but still probably too theoretical. Further, eventually one will encounter measure spaces that aren't based on the real numbers and the Lebesgue measure,

Yes, this is a good thing. One doesn't understand a structure until one understands which parts of a structure are forcing which properties. Moreover, this supplies useful counterexamples that helps one understand what sort of things one necessarily will need to invoke if one wants certain results.

Comment author: Will_Sawin 17 January 2011 08:53:46PM 3 points [-]

It is much easier to understand what the words in the definition of the gauge integral mean. It is harder to understand why they are there.

Comment deleted 18 January 2011 06:23:02AM [-]
Comment author: JoshuaZ 18 January 2011 02:48:14PM 0 points [-]

Yes, I did make it to the end of the sentence. But I misinterpreted the sentence to be having two distinct criticisms when there was only one.

Comment author: wbcurry 17 January 2011 06:04:31PM 6 points [-]

Non-relativistic Quantum Mechanics: Sakurai's Modern Quantum Mechanics

This is a textbook for graduate-level Quantum Mechanics. It's advantages over other texts, such as Messiah's Quantum Mechanics, Cohen-Tannoudji's Quantum Mechanics, and Greiner's Quantum Mechanics: An introduction is in it's use of experimental results. Sakurai weaves in these important experiments when they can be used to motivate the theoretical development. The beginning, using the Stern-Gerlach experiment to introduce the subject, is the best I have ever encountered.

Comment author: orthonormal 17 January 2011 06:31:56PM 0 points [-]

I second the recommendation, although I haven't read other textbooks.

Comment author: cursed 28 January 2011 08:42:11AM 4 points [-]

What are the prerequisites for reading this? What level of mathematics and background of classical physics?

Comment author: Mimi 19 March 2012 02:22:30AM 0 points [-]

Why don't you like Cohen-Tannoudji?

Comment author: komponisto 17 January 2011 06:22:42PM 18 points [-]

Music theory: An Introduction to Tonal Theory by Peter Westergaard.

Comparing this book to others is almost unfair, because in a sense, this is the only book on its subject matter that has ever been written. Other books purporting to be on the same topic are really on another, wrong(er) topic that is properly regarded as superseded by this one.

However, it's definitely worth a few words about what the difference is. The approach of "traditional" texts such as Piston's Harmony is to come up with a historically-based taxonomy (and a rather awkward one, it must be said) of common musical tropes for the student to memorize. There is hardly so much as an attempt at non-fake explanation, and certainly no understanding of concepts like reductionism or explanatory parsimony. The best analogy I know would be trying to learn a language from a phrasebook instead of a grammar; it's a GLUT approach to musical structure.

(Why is this approach so popular? Because it doesn't require much abstract thought, and is easy to give students tests on.)

Not all books that follow this traditional line are quite as bad as Piston, but some are even worse. An example of not-quite-so-bad would be Aldwell and Schachter's Harmony and Voice Leading; an example of even-worse would be Kotska and Payne's Tonal Harmony, or pretty much anything you can find in a non-university bookstore (that isn't a reprint of some centuries-old classic like Fux).

Comment author: soundchaser 18 January 2011 04:32:09AM 2 points [-]

I have been using Harmony and Voice Leading for a little while. Is An Introduction to Tonal Theory really that much better?

I've always felt that the way they explain concepts is very hand wavy and doesn't really explain anything and I tend to prefer things to be more mathematical or abstract.

I'll probably pick this book up on your suggestion.

Comment author: komponisto 19 January 2011 01:27:10AM 4 points [-]

I have been using Harmony and Voice Leading for a little while. Is An Introduction to Tonal Theory really that much better?

Yes.

Don't get me wrong, Aldwell and Schachter are about the best you can do while still remaining in the traditional "vocabulary of chords" paradigm. (You can even see how they tried to keep the number of "chords" down to a minimum.) Unfortunately, that paradigm is simply wrong.

Also, Aldwell and Schachter, brilliant musicians though they may be (especially Schachter), lack the deeper intellectual preoccupations that Westergaard possesses in abundance. One should perhaps think of their book as being written for students at Mannes or Julliard, and of Westergaard's as being written for students at Columbia or Princeton. (There is a certain literal truth to these statements.)

I've always felt that the way they explain concepts is very hand wavy and doesn't really explain anything and I tend to prefer things to be more mathematical or abstract.

You'll love ITT.

Comment author: TessPope 11 February 2011 03:00:31PM 1 point [-]

"One should perhaps think of their book as being written for students at Mannes or Julliard and of Westergaard's as being written for students at Columbia or Princeton. (There is a certain literal truth to these statements.)"

As a graduate of Juilliard I am curious about this assertion. Care to elaborate? Not that I personally have ever had much use as a performer for abstract notions about music theory. My experience has been that it gets in the way of actually performing music. Which leads to the question 'why should this be so' ? Those of my colleagues who were great adepts at theory were uninspired performers of the music they seemed to understand so well. All head and no heart. But why? I can understand that they are different skill sets, but why should they not be complementary skill sets?

I imagine that on this site, alarm bells may go off as I make an observation from experience, but I do not think that it would be possible to use any sort of methodology or system analysis to determine who is and who is not an inspired performer. Just try figuring out how orchestral auditions are run! Now that is a sloppy business!

Regarding textbooks: have any of you read W.A. Mathieu's

W.A. Mathieu Harmonic Experience: Tonal Harmony from Its Natural Origins to Its Modern Expression (1997) Inner Traditions Intl Ltd. ISBN 0-89281-560-4.

Comment author: komponisto 12 February 2011 04:40:48AM *  5 points [-]

As a graduate of Juilliard I am curious about this assertion. Care to elaborate? Not that I personally have ever had much use as a performer for abstract notions about music theory. My experience has been that it gets in the way of actually performing music. Which leads to the question 'why should this be so' ? Those of my colleagues who were great adepts at theory were uninspired performers of the music they seemed to understand so well. All head and no heart. But why? I can understand that they are different skill sets, but why should they not be complementary skill sets?

It's a complicated question, but the short answer is that what usually passes for "music theory" is the wrong theory. At least, it's certainly the wrong theory for the purposes of turning people into inspired performers, because as you point out, it doesn't.

But then, if you'll forgive my cynicism, that isn't the purpose of music theory class, any more than the purpose of high-school Spanish class is to teach people Spanish. The purpose of such classes is to provide a test for students that's easy to grade them on and makes the school look good to outside observers.

(Nor, by the way, do students typically show up at Juilliard for the purpose of turning themselves from uninspired into inspired performers; rather, in order to get there in the first place they already have to be "inspired enough" by the standards of current musical culture, and are there simply for the purposes of networking and career-building.)

But music theory isn't inherently counterproductive to or useless for becoming a good performer or composer; it's just that you need a different theory for that. Ultimately, inspired performers are that way because they know certain information that their less-inspired counterparts don't; to see what this sort of information looks like when written down, see Chapter 9 of Westergaard. (And after reading that chapter, tell me if you still think that knowledge of music theory "gets in the way of actually performing music".)

Comment author: Spurlock 20 January 2011 01:56:47PM 3 points [-]

I've always found traditional music theory to be useless if not actively damaging (seems to train people in bad thought habits for writing/appreciating music). Can you summarize Westergaard's approach? I know why the typical methods are bad, but I'm interested in what exactly his alternative is.

Comment author: komponisto 20 January 2011 09:21:06PM *  8 points [-]

Can you summarize Westergaard's approach? I know why the typical methods are bad, but I'm interested in what exactly his alternative is.

In ITT itself, Westergaard offers the following summary (p.375):

  1. we can generate all the notes of any tonal piece from the pitches of its tonic triad by successive application of a small set of operations, and moreover

  2. the successive stages in the generation process show how we understand the notes of that piece in terms of one another

(This, of course, is very similar to the methodology of theoretical linguistics.)

Westergaard basically considers tonal music to be a complex version of species counterpoint --- layers upon layers of it. He inherits from Schenker the idea of systematically reversing the process of "elaboration" to reveal the basic structures underlying a piece (or passage) of music, but goes even further than Schenker in completely explaining away "harmony" as a component of musical structure.

Notes are considered to be elements of lines, not "chords". They operations by which they are generated within lines are highly intuitive. They essentially reduce to two: step motion, and borrowing from other lines.

A key innovation of Westergaard is to unify pitch-operations and rhythmic operations. Every operation on pitch occurs in the context of an operation on rhythm: segmentation, delay, or anticipation of a timespan. This is arguably implicit in Schenker (and even in species counterpoint itself) but Westergaard makes it explicit and systematic. Hence he arrives at his "theory of tonal rhythm" which is the core of the book (chapters 7-9).

The table of contents, at the level of chapters, should give you an idea of how different Westergaard's book is from other texts:

Part I. Problems and Assumptions

  1. What are we talking about?
  2. Notes
  3. Lines

Part II. A First Approximation: Species Counterpoint

4. Species counterpoint
5. Simple species
6. Combined species

Part III A little closer to the real thing -- a theory of tonal rhythm

7. Notes, beats and measures
8. Phrases, sections, and movements
9. Performance

Appendix: Constructing a pitch system for tonal music

EDIT: 1,2,3 under Part II and Part III should be 4,5,6 and 7,8,9 respectively, which is what I typed. I mostly like the comment formatting system here, but that is one hell of a bug.

EDIT2:: fixed.

Comment author: arundelo 21 January 2011 01:55:56AM *  1 point [-]

Thanks for the summary. I may get this book.

You can defeat automatic list formatting if your source code looks like this:

4\. Species counterpoint##
5\. Simple species##
6\. Combined species

except with spaces instead of "#" (to prevent the list items from being wrapped into one paragraph). Edit: If the list items have blank lines between them, the trailing spaces are not necessary.

(The creator of the Markdown format says "At some point in the future, Markdown may support starting ordered lists at an arbitrary number.")

Comment author: komponisto 21 January 2011 07:14:20PM 0 points [-]

Thanks, fixed.

Comment author: Spurlock 21 January 2011 03:18:08PM 0 points [-]

Interesting, thanks. I don't know if that sounds right or even useful, but it definitely sounds interesting, I'll be putting it on my "books to check out" list. I get the impression that it's very reductionist approach, which is a promising sign.

Comment author: bgaesop 17 January 2011 08:10:21PM 2 points [-]

I would like to request a recommendation for a text that introduces one to Utilitarianism.

Comment author: lukeprog 17 January 2011 08:18:01PM *  4 points [-]

I don't read much on normative ethics, but Smart & Williams' Utilitarianism: For and Against has some good back-and-forth on the major issues, at least up to 1973. The other advantage of this book is that it's really short.

But there are probably better books on the subject I'm just not aware of.

Comment author: bgaesop 17 January 2011 11:25:45PM 0 points [-]

I have put it on hold at my school's library. Thanks! I'll try to post a review once I read it, if I can find an appropriate space and time.

Comment author: michaba03m 18 January 2011 11:23:51PM 0 points [-]

I have been studying utilitarianism in particular in quite some depth as part of my university degree (PPE). And yes I would DEFINITELY recommend that book, it is excellent. Also, of couse, Mill's book itself is very important to read as it had such a significant effect on ethics and politics, though I wouldn't say that he is necessarily the best representative of what utilitarians generally believe (the devil's in the details).

Another very simple, straightforward & lucid book is Roger Crisp's 'Routledge Philosophy Guidebook to Mill on Utilitarianism', definitely recommended. Or anything by Crisp, on that matter.

If you're still hungry for more, still on level one/two is 'Mill's Utilitarianism: Critical Essays' by Lyons.

Enjoy!

Comment author: YoungFolks 12 February 2011 03:33:52AM 0 points [-]

I was recently introduced to utilitarianism, more precisely, Mill's Utilitarianism, because I was assigned to do a speech on it for a class. I found the work fascinating and frustrating, and I immediately sought my professor and the library for help in better understanding Mill's views. I found the book by Lyons and I've been engrossed by it. The different critical essays on different parts of utilitarianism have made it so much more clear to me. I like how there are essays with different takes on utilitarianism, some that argue for/against rule-utilitarianism, or for/against act-utilitarianism, and some that just explain it in more depth without choosing a side. This book and Mill's own Utilitarianism are the only books I've read so far, but both are excellent.

Can someone recommend good books on Bentham's Utilitarianism?

Comment author: joshkaufman 17 January 2011 08:37:17PM 17 points [-]

Business: The Personal MBA: Master the Art of Business by Josh Kaufman.

I'm the author, so feel free to discount appropriately. However, the entire reason I wrote this book is because I spent years searching for a comprehensive introductory primer on business practice, and I couldn't find one - so I created it.

Business is a critically important subject for rationalists to learn, but most business books are either overly-narrow, shallow in useful content, or overly self-promotional. I've read thousands of them over the past six years, including textbooks.

Business schools typically fragment the topic into several disciplines, with little attempt to integrate them, so textbooks are usually worse than mainstream business books. It's possible to read business books for years (or graduate from business school) without ever forming a clear understanding of what businesses fundamentally are, or how they actually work.

If you're familiar with Charlie Munger's "mental model" approach to learning, you'll recognize the approach of The Personal MBA - identify and master the set of business-related mental models that will actually help you operate a real business successfully.

Because making good decisions requires rationality, and businesses are created by people, the book spend just as much time on evolutionary psychology, decision-making in the face of uncertainty, and anti-akrasia as it does on traditional business topics like marketing, sales, finance, etc.

Peter Bevelin's Seeking Wisdom is comparable, but extremely dry and overly focused on investment vs. actually running a business. The Munger biography Poor Charlie's Almanack contains some helpful details about Munger's philosophy and approach, but is not comprehensive.

If anyone has read another solid, comprehensive primer on general business practice, I'd love to know.

Comment author: lukeprog 18 January 2011 01:49:08AM 3 points [-]

Rather phenomenal Amazon reviews you have, sir.

Comment author: FrF 18 January 2011 02:41:14AM *  2 points [-]

I remember the interview Josh did with Ben Casnocha as being very interesting. (Site contains links to streaming video and MP3 download + written interview summary.)

Comment author: joshkaufman 18 January 2011 08:47:16PM 0 points [-]

Thanks - glad people are finding it useful.

Comment author: Cyan 18 January 2011 02:42:33AM 2 points [-]

I'm reading it now. I fully endorse this recommendation, but I haven't read any other business books, so take that for what it's worth.

Comment author: MichaelGR 18 January 2011 05:11:42PM *  2 points [-]

I've added it to my list. I'm currently reading Poor Charlie's Almanack and liking it a lot so far.

The best business book I've read is probably The Essays of Warren Buffett (second ed.), but it's certainly not exhaustive in what it covers.

Update: I've got my copy from Amazon.ca (really fast shipping - 2 days). Will probably have a chance to read it in February.

Comment author: Dr_Manhattan 23 January 2011 10:16:23PM 3 points [-]

I like the book so far, it seems to pretty much a solid implementation of Munger's approach.

Spends a bit too much energy dissuading me from business school, including some arguments I found rhetorical (e.g. biz. schools started from people measuring how many seconds a railway worker does something or other. by this logic we should outlaw chemistry), but it might be useful to someone (though there are quite a few people in line to take their places).

Comment author: Duke 21 July 2011 03:17:46AM 3 points [-]

This book, or, to be accurate, the 20 or so pages I read, are terrible. For someone who prefers dense and thorough examinations of topics, The Personal MBA is cotton candy. It is viscerally pleasing, but it offers little to no sustenance. My advice: don't get an MBA or read this book.

The mistake I made was considering the author's appearance in this thread as strong evidence that his book would offer value to a rationalist. In fact, the author is a really good marketer whose book has little value to offer. Congratulations to him, however, since he got me to buy a brand-new copy of a book, something I rarely do.

Comment author: joshkaufman 27 July 2011 05:08:43AM 9 points [-]

Wow, Duke - that's a bit harsh.

It's true that the book is not densely written or overly technical - it was created for readers who are relatively new to business, and want to understand what's important as quickly as possible.

Not everyone wants what you want, and not everyone values what you value. For most readers, this is the first book they've ever read about how businesses actually operate. The worst thing I could possibly do is write in a way that sounds and feels like a textbook or academic journal.

I don't know you personally, but from the tone of your comment, it sounds like you're trying to signal that you're too sophisticated for the material. That may be true. Even so, categorical and unqualified statements like "terrible" / "cotton candy" / and "little value to offer" do a disservice to people who are in a better position to learn from this material than you are.

That said, I'll repeat my earlier comment: if you've read another solid, comprehensive primer on general business practice, I'd love to hear about it.

Comment author: Duke 28 July 2011 03:16:05AM 3 points [-]

I think the title--and especially the subtitle, " Mastering the Art of Business,"--signals that the book will be a thorough examination of business principles. As well, I think that hocking your book in a thread called "The Best Textbooks on Every Subject" signals that the book will be, at least, textbook-like in range, complexity and information containment. You now call your book "not densely written or overly technical." I call it cotton candy.

Comment author: [deleted] 28 July 2011 03:19:09AM 3 points [-]

I upvote you solely for the chutzpah of your self-promotion.

Which, in hindsight, is mostly what you're selling.

Comment author: Duke 08 August 2011 03:52:45AM 5 points [-]

For the sake of clarity, my criticism of Josh's book was developed within the context of Josh promoting his book in a LW thread titled "The Best Textbooks on Every Subject."

Comment author: joshkaufman 10 August 2011 09:23:01PM 6 points [-]

Useful clarification. In that case, you should know that the book is currently being used by several undergraduate and graduate business programs as an introductory business textbook.

The book is designed to be a business primer ("an elementary textbook that serves as an introduction to a subject of study"), and business is a very important area of study that rewards rationality. At the time of my original post, no one had recommended a general business text. That's why I mentioned the book in this thread.

I appreciate your distaste for perceived self-promotion: as a long-time LW lurker, my intent was to contribute a resource LW readers might find valuable, nothing more.

If you're interested in the general topic and want a more academic treatment, you may enjoy Bevelin's Seeking Wisdom. I found it a bit disorganized and overly investment-focused, but you may find it's more to your liking.

Comment author: lukeprog 06 November 2011 12:13:14AM 5 points [-]

My summary of chapter 9, for anyone who cares:

Fear kills work. Inspire coworkers by showing them appreciation, courtesy, and respect. Show them they're important. Get them to work in their comparative advantage, and where they are intrinsically motivated. Explain the reasons why you ask for things. Someone must be responsible and accountable for each task. Avoid clanning; get staff to work together on shared projects and enjoy relaxation time together. Measure things, to see what works. Avoid unrealistic expectations. Shield workers from non-essential bureaucracy.

Comment author: realitygrill 17 January 2011 10:10:06PM 5 points [-]

Subject: Economics

Recommendation: Introduction to Economic Analysis (www.introecon.com)

This is a very readable (and free) microecon book, and I recommend it for clarity and concision, analyzing interesting issues, and generally taking a more sophisticated approach - you know, when someone further ahead of you treats you as an intelligent but uninformed equal. It could easily carry someone through 75% of a typical bachelor's in economics. I've also read Case & Fair and Mankiw, which were fine but stolid, uninspiring texts.

I'd also recommend Wilkinson's An Introduction to Behavioral Economics as being quite lucid. Unfortunately it is the only textbook out on behavioral econ as of last year, so I can't say it's better than others.

Comment author: alexflint 17 January 2011 11:12:14PM 4 points [-]

Machine learning: Pattern Recognition and Machine Learning by Chris Bishop

Good Bayesian basis, clear exposition (though sometimes quite terse), very good coverage of the most modern techniques. Also thorough and precise, while covering a huge amount of material. Compared to AI: A modern approach it is much more clearly based in Bayesian statistics, and compared to Probabilistic robotics it's much more modern.

Comment author: PhilGoetz 23 January 2011 08:18:32PM 8 points [-]

Bishop, vs Russell & Norvig, are not in the same category. There's only two chapters in R&N that overlap with Bishop.

Within the category of planning, symbolic AI, and agent-based AI, I recommend Russell & Norvig, "Artificial Ingelligence: A Modern Approach", or Luger & Stubblefield, "Artificial Intelligence". They are aware of non-symbolic approaches and some of the tradeoffs involved. I do not recommend Charniak & McDermott, "An intro to artificial intelligence", or Nilsson, "Principles of artificial intelligence", or Winston, "Artificial Intelligence", as they go into too much detail about symbolic techniques that you'll probably never use, like alpha-beta pruning, and say nothing about non-symbolic techniques. A more complete treatement of symbolic AI is Barr & Feigenbaum, "The Handbook of Artificial Intelligence", but that's a reference work, and I'm recommending textbooks. I do recommend a symbolic AI reference work, Shapiro, "Encyclopedia of Artificial Intelligence", because the essays are reasonably short and easy to read.

Within machine learning, data mining, and pattern recognition, I haven't read Bishop's work. Mannila & Smyth, "Principles of Data Mining", are often used; but maybe just because they're from MIT. Larose, "Data mining methods and models", is okay, as is its companion volumne whose name I forget. My favorite is Data Mining: Practical Machine Learning Tools and Techniques (Second Edition), by Ian H. Witten and Eibe Frank. It is brief, to the point, and gives coding examples using Weka.

The best advice I can give related to statistical modeling is to look up your technique in the SAGE series, and buy the SAGE books on it. They cost about $16 apiece, less used on amazon, and are short yet detailed. Now, I don't mean the books SAGE tries to sell you on their website. I mean the series of about 200 small light-green-cover paperbacks that they for some reason don't tell you about on their website.

But if you're reading this level of detail, it means you're going to be a specialist trying to implement or improve algorithms, and you're going to need to read entire books on each subject.

Comment author: lukeprog 18 January 2011 12:26:29AM 2 points [-]

Added the recommendations by joshkaufman, realitygrill, and alexflint.

Thanks, gang! Keep 'em coming.

Comment author: Alex_Altair 18 January 2011 04:30:36AM 4 points [-]

Subject: Electromagnetism, Electrodynamics

Recommendation: Introduction to Electrodynamics by David J. Griffiths

I first received this textbook for a sophomore-level class in electrodynamics. It was reused for a few more classes. I admit that I don't have much to compare it with, though I have looked at Feynman's lectures, a couple giant silly freshman physics tomes, and J. D. Jackson's Electrodynamics, and I know what textbooks are like in general.

I was repeated floored by the quality of this book. I felt personally lead through the theory of electrodynamics. In general, he does go from the simple and specific to the complex and general, as any mind requires. But at every stage, he knows exactly where there is risk of conceptual confusion, and he knows exactly how to correct it. He brings every clarification and result back to the the fundamentals of the subject, and he keeps you radiantly aware of the context. After this kind of developed enlightenment, you walk away with a rationalist's mastery, at least in this specific subject. He does all this, from vector calculus review to special relativity, in 2 centimeters thick.

Comment author: golwengaud 25 January 2011 09:46:40PM 4 points [-]

I found that Griffiths is an excellent undergraduate textbook. It does, as you say, provide an astoundingly good conceptual understanding of electrodynamics.

I was very disappointed, however, at the level of detail and rigour. Jackson, (in my limited experience), while it may not provide the same amount of explanation at an intuitive level, shows exactly what happens and why, mathematically, and in many more cases.

This speaks to an important distinction between undergraduate and graduate textbooks. Graduate textbooks provide more detail, more rigour, and more material, while undergraduate textbooks provide insight.

There is something of a similar situation in quantum mechanics: Townsend's /A Modern Approach to Quantum Mechanics/ is very much an undergrad textbook, and indeed something of a dumbed-down version of (the first half of) Sakurai's /Modern Quantum Mechanics/. At this point I strongly prefer Sakurai, but I don't think I would be able to understand it without all the time I spent studying Townsend's more elementary presentation of the same approach.

Comment author: Anatoly_Vorobey 25 January 2011 10:57:19PM 3 points [-]

To give yet another example, I've been slowly trying to teach myself GR, and while I love the approach and the rigor of Wald's General Relativity, it was too hard for me to follow on its own terms. I found that Schutz's A First Course in General Relativity provides both the insight and better grounding in some of the necessary math (tensor analysis, getting used to Einstein's summation convention, using the metric to flip indices around) through gentler approach and richer examples. Having studied Schutz for some time, I feel (almost) ready to come back to Wald now.

Comment author: Davidmanheim 18 January 2011 03:30:42PM 2 points [-]

On systems theory, I'll recommend "Thinking in Systems: A Primer" is a great general audiences book, with a great nontechnical approach.If you are looking for something more mathematical, you'll need to ask someone else; I'm just not well read enough. (Despite being a math major back in school.)

"The Fifth Discipline: The Art & Practice of The Learning Organization" is a great book, but not as useful for systems theory in general, it's a more domain specific book. (I would recommend it, but not as the best book on the subject generally)

"Introduction to Systems Thinking" by Kim is just not as good; it's a fine book, but small and not at all comprehensive.

There are some great, slightly more technical books on the subject, like An Introduction to General Systems Thinking by Weinberg, as well, I am sure, as others. I haven't read enough of them to say that that specifically stands out among technical books on the subject. (If anyone has recommendations on the technical side, I'd love to hear them, as I would like to see more.)

Comment author: PeterisP 18 January 2011 11:19:30PM 0 points [-]

I haven't read the books you mention, but it seems that Sterman's 'Business Dynamics: Systems thinking and modeling for a complex world' covers mostly the same topics, and it felt really well written, I'd recommend that one as an option as well.

Comment author: Davidmanheim 19 January 2011 02:57:10PM 0 points [-]

I have not read it, but the title and the reviews on amazon seem to imply that the book isn't about systems theory, it's about applications of systems theory to business and economics, two great applications, but not the subject itself. Physics books may be great, and they may need to explain math, but they are not math books. If this is indeed a business book, I'd hesitate to recommend it as a book on systems theory.

Comment author: PeterisP 19 January 2011 09:06:01PM *  0 points [-]

It goes on from the reasons of systems thinking through the theoretical foundation, the maths used, and the practical applications and pretty much all common types of issues seen in real world.

It's about 5 times larger volume (~1000 A4 pages) than the Meadows' "Thinking in Systems", so not exactly textbook format, but covers the same stuff quite well and more. Though, it does spend much of the second half of the book focusing almost exclusively on practical development of system dynamics models.

Comment author: lukeprog 18 January 2011 05:53:35PM 0 points [-]

Added the recommendations by Davidmanheim and Alex_Altair.

I'd personally appreciate a rule-following recommendation on A.I.

Comment author: Dr_Manhattan 18 January 2011 06:03:08PM *  0 points [-]

(This title already mentioned, but not as a top-level comment) For general Artificial Intelligence, Artificial Intelligence a Modern Approach by Russell and Norvig. It's very broad but still deep enough to get a feel for a lot of areas, with some advantages of scale due to certain exmples and consistent notation being used across many areas. It's also a much easier read than Bishop's ML book already mentioned for Machine Learning stuff, though Bishop's book is much more specialized.

To get an idea of the difference in scope AIMA covers planning algorithms, NLP, decision theory and even FAI (though pretty much by mention only).

Comment author: lukeprog 18 January 2011 07:06:27PM 0 points [-]

But, have you ready any other books on AI, to which you can compare it?

Comment author: Dr_Manhattan 18 January 2011 07:26:48PM 0 points [-]

Not this general kind of AI coverage, but I've read a number of books in data mining and some specialized aspects of AI such as Bayes nets and NLP. It compares very favorably in terms of presentation quality; I am not aware of another book this broad which was potentially worth reading based on my "information olfactory sense" (I'd like to hear of one if anyone has a suggestion) .

Comment author: lukeprog 19 January 2011 10:46:42PM *  1 point [-]

Russell and Norvig do seem to have the only general A.I. textbook out there that I can find...

Comment author: bgaesop 19 January 2011 08:31:22AM 2 points [-]

I would like to request a book on Game Theory. I went to my school's library and grabbed every book I could find, and so I have Introduction to Game Theory by Peter Morris, Game Theory 2nd Edition by Guillermo Owen, Game Theory and Strategy by Philip Straffin, Game Theory and Politics by Steven Brams, Handbook of Game Theory with Economic Applications edited by Aumann and Hart, Game Theory and Economic Modeling by David Kreps, and Gaming the Vote by William Poundstone because I also like voting theory.

My brief glances make Game Theory and Strategy look like a fun, low level read that I'll probably start with to whet my appetite for the subject. Introduction to Game Theory looks like a good, well written intro textbook, but it was written in 1940 and was only updated once in 1994, and I would hope something new would have happened in that time. Game Theory 2nd Edition looks like a good, moderately modern (1982) and incredibly boring book. The others look worse.

I'll read at least portions of all of them and at least two or three completely unless somebody suggests anything. If no one does before I read them I'll post an update.

Comment author: lukeprog 19 January 2011 08:26:31PM *  1 point [-]

I would like to request a book recommendation on probability theory.

Following the rules if possible.

Comment author: Matt_Simpson 21 January 2011 02:29:07PM *  1 point [-]

I was just about to ask the same question, specifically for a measure theoretic treatment of probability theory. I've only read/still am reading Measure Theory and Probability Theory by Athreya and Lahiri for the second of a two course sequence and am not too impressed. For one, there are many typos that decrease the readability unless you're already familiar with measure theory and functional analysis (I was not). I haven't read any other texts of this nature, so I can't make any comparisons.

Comment author: [deleted] 27 January 2011 07:30:47PM *  6 points [-]

Feller comes in two volumes, and goes from extremely introductory to measure theory in the second volume. It's a classic and Feller is famous for his writing style, and so this is probably the best book. I remember finding it confusing once upon a time, but that was probably because I was too young and not because of the book.

Ross is elementary, and isn't a measure-theoretic approach, and has lots of applications (e.g. to queuing theory and operations). It's handy as a "gimme the facts" kind of book -- if you want to look up common distributions and formulae you'll find them in Ross faster than anywhere else -- but it doesn't have all the mathematical foundations you might want.

Koralov and Sinai is a measure-theory based probability course. The second half of the book has stochastic processes, martingales, etc. If you don't know any probability at all (let's say... haven't seen the Bernoulli distribution derived) or if you haven't seen measure theory, it's probably not intuitive enough to be your first textbook. I had no complaints with the presentation; it was all straightforward enough.

Basically, I'd split the difference between elementary and advanced by using Feller; he includes EVERYTHING so you can safely skip what you know and read what you don't.

Comment author: Dr_Manhattan 27 January 2011 09:21:42PM 1 point [-]

Feller is very good, though I haven't even finished vol1. I also like Tijms for real beginners - easy and fun, good examples. http://www.amazon.com/Understanding-Probability-Chance-Rules-Everyday/dp/0521701724/ref=sr_1_1?ie=UTF8&qid=1296163232&sr=8-1

Comment author: lukeprog 27 January 2011 10:05:52PM 0 points [-]

Awesome, thanks!

Comment author: Vlad 29 April 2011 12:18:52PM 1 point [-]

The best introductory book I've read is Chance in Biology: Using Probability to Explore Nature by Mark Denny and Steven Gaines. While most introductory books have mainly examples from games of chance, this book uses examples from physics, chemistry and biology. It's very accessible and it takes you very fast from the basic rules of probability theory to useful examples.

I would also recommend Jaynes' lectures. They're more informal than the book (and also free :D). These I think are the best for quickly understanding the "subjectivist" approach to probability theory.

Comment author: lukeprog 20 January 2011 09:59:09PM 3 points [-]

In the wake of publishing Scientific Self-Help: The State of Our Knowledge, I realized there is another subject on which I have read at least three textbooks: self-help!

Subject: Self-Help

Recommendation: Psychology Applied to Modern Life by Weiten, Dunn, and Hammer

Reason: Tucker-Ladd's Psychological Self-Help is a 2,000 page behemoth of references from a passionate, life-long researcher in self-help. It was a work-in-progress for 20 years, and never mass-published. It's an excellent research resource, though it's now out-of-date. John Santrock's Human Adjustment is a genuine university textbook on self-help, but it is not as mature, well-organized, or well-written as Weiten, Dunn, and Hammer's Psychology Applied to Modern Life.

Comment author: fbs42 23 January 2011 02:43:15PM 0 points [-]

What a wondrous idea! And, the contributions to date are outstanding. Thank you!

Comment author: squigglier 24 January 2011 05:33:59AM 1 point [-]

I haven't had much success with textbooks. I have found them to be mostly boring and riddled with errors. I interpret boredom to mean that I'm not learning anything.

Here's a possible explanation for the boringness. Are you familiar with the experience of not being able to understand how you didn't get something, right after you've got it? The same presumably applies in the minds of professors.

It's hard for them to imagine not understanding the ideas. One can't know what the reader knows and doesn't know and what his misconceptions are. Teaching generations of students helps, but not much, and it won't help at all with tacit knowledge communicated face-to-face, but not via text.

Incidentally, that's probably why textbooks are so full of mistakes: not only do they contain arcane symbols which cause typos, but, being boring, nobody reads them anyway and the errors remain uncorrected.

The solution I think is to make two texts: one main text, which can be edited online to fix errors, and accompanying notes written by readers, with links to better material wherever possible.

Comment author: lukeprog 26 January 2011 05:40:49AM 3 points [-]

If textbooks don't work for you very often, what does work for you?

Comment author: [deleted] 26 January 2011 05:06:45PM 10 points [-]

Everyone should pass this post along to their favorite professors.

Professors will have read numerous textbooks on several subjects, and can often say which books work best for their students.

Comment author: BrandonReinhart 29 January 2011 07:04:37AM 2 points [-]

Thank you for this post. It is profoundly useful. I noted it when it first appeared and recently had the need for a textbook on a subject. Came over here and found a great one.

Comment author: jsteinhardt 29 January 2011 04:31:28PM 5 points [-]

For topology, I prefer Topology by Munkres to either Topology by Amstrong or Algebraic Topology by Massey (the latter already assumes knowledge of basic topology, but the second half of Munkres covers some algebraic topology in addition to introducing point-set topology in the first half).

Both Armstrong and Massey try to make the subject more "intuitive" by leaving out formal details. I personally just found this confusing. Munkres is very careful about doing everything rigorously at the beginning, but this lets him cover much more material more quickly later, because he can safely talk about something without wondering whether the reader will correctly guess an implication, because the reader (in theory) understands the background material completely and will be able to tell what is going on.

Munkres' treatment is also far more comprehensive.

Munkres also has a lot of really good exercises, although I didn't get far enough into the other two books to really evaluate how good their exercises are.

One caveat: in topology it is easy to push definitions around without understanding what's going on. It helps to be able to draw pictures of e.g. Haussdorf condition to be able to figure out what's going on.

Comment author: etymologik 31 January 2011 07:38:09AM 3 points [-]

Recommended for LINGUISTICS: "Contemporary Linguistics", by William O'Grady, John Archibald, Mark Aronoff, & Janie Rees-Miller. Truly comprehensive, addressing ALL the areas of interesting work in linguistics -- phonetics, phonology, morphology, syntax, semantics, historical linguistics, comparative linguistics & language universals, sign languages, language acquisition and development, second language acquisition, psycholinguistics, neurolinguistics, sociolinguistics & discourse analysis, written vs spoken language, animal communication, & computational/corpus linguistics. Each chapter is sharp & targetted; you will really know what you want to read next after studying this text.

NOT recommended: "Linguistics: An Introduction to Linguistic Theory", edited by Victoria A. Fromkin & authored by Bruce Hayes, Susan Curtiss, Anna Szabolcsi, Tim Stowell, Edward Stabler, Dominique Sportiche, Hilda Koopman, Patricia Keating, Pamela Munro, Nina Hyams, & Donca Steriade. This text provides a solid guide to generative phonology, generative syntax, and formal semantics -- but only in their mainstream (aka Chomskian) formulations, and with no reference to actual language use (which, for theoretical reasons, is anathema to the Chomskian crowd). Interestingly, at least 8 of the authors I recognize as faculty from UCLA, which makes the text a bit ingrown for my taste.

NOT recommended: "Syntax: A Generative Introduction", by Andrew Carnie. First problem: This book covers syntax and only syntax, and does so solely from a generative perspective. Second problem: Although Carnie is a reknowned expert in Irish Gaelic syntax and doubtless knows his stuff, he can't write a clear expository textbook to save his soul. This is the most confusing book on linguistics that I've ever read.

Comment author: etymologik 31 January 2011 07:49:48AM 1 point [-]

I would also like to recommend two superb encyclopedia-style works on linguistics:

(1) "The Cambridge Encyclopedia of Language", by David Crystal

(2) "The Cambridge Encyclopedia of the English Language," by David Crystal

Both are characterized by lot of short articles, sidebars, pictures, cartoons, and examples of texts to the point at hand. I read them both cover to cover, and have refered to them again and again when beginning to explore a new topic in the field.

Comment author: BrandonReinhart 07 February 2011 01:43:33AM 2 points [-]

Request for textbook suggestions on the topic of Information Theory.

I bought Thomas & Cover "Elements of Information Theory" and am looking for other recommendations.

Comment author: fiddlemath 07 February 2011 01:47:12AM 5 points [-]

MacKay's Information Theory, Inference, and Learning Algorithms may not be exactly what you're looking for. But I've heard it highly recommended by people with pretty good taste, and what I've read of it is fantastic. Also, the pdf's free on the author's website.

Comment author: john-lawrence-aspden 26 May 2011 09:46:15PM 1 point [-]

I highly recommend this book, but then it's currently my introduction to both Information Theory and Bayesian Statistics, and I haven't read any others to compare it to. I find it difficult to imagine a better one though.

Clear, logical, rigorous, readable, and lots of well chosen excellent exercises that illuminate the text.

Comment author: lukeprog 07 February 2011 02:01:12AM 1 point [-]

Updated again. Thanks, people! Keep 'em coming!

Comment author: fr00t 15 February 2011 11:38:22PM *  2 points [-]

I would like to request a recommendation for a text that provides a comprehensive introduction to Lisp, preferably one with high readability.

Comment author: diegocaleiro 18 February 2011 10:11:26PM 0 points [-]

I would like a general introduction to Programming.

Computational Neuroscience would also be great..... though the field is kind of new....

Comment author: kjmiller 08 October 2011 03:24:35PM 0 points [-]

Theoretical Neuroscience by Dayan and Abbot is a fantastic introduction to comp neuro, from single-neuron models like Hodgkin-Huxley through integrate-and-fire and connectionist (including Hopfield) nets up to things like perceptrons, reinforcement learning models. Requires some comfort with Calculus.
Computational Exploration in Cog Neuro by Randall O'Reilly purports to cover the similar material on a slightly more basic level, including lots of programming exercises. I've only skimmed it, but it looks pretty good. Kind of old, though, supposedly Randy's working on a new edition that should be out soon.

Comment author: Barry_Cotter 21 February 2011 08:48:52AM 1 point [-]

Structure and Implementation of Computer Programs

How to design Programs

The Little Schemer

HTDP teaches Scheme, SICP teaches computer science concepts using Scheme.

Comment author: [deleted] 21 February 2011 12:48:03AM 1 point [-]

Any recommendations for a textbook on cryptography?

Comment author: dlthomas 08 November 2011 08:56:20PM 3 points [-]

The math, or application thereof?

For the latter, Applied Cryptography, by Bruce Schneier is the standard response, and surprisingly readable. I've read other books in the field, but nothing I can think of that's quite as much a "textbook", so this recommendation may or may not officially count.

And of course, a caveat applies to any book on cryptography: don't read it and start coding your own algorithms - anyone can invent a cryptosystem he can't break himself. If you're planning on doing development, the only safe way to handle this stuff is to use well reviewed, well maintained libraries. A textbook will give you a sense of what's available and how things might fit together.

Comment author: Swimmer963 10 March 2011 12:02:09AM 1 point [-]

Can anyone think of a good textbook on research in nursing? The one I have is abysmal and I literally cannot read it, thus I have a C in the class. Something in English might help. (I'm taking the class in French and although I'm almost equally fluent in both, I do find it harder work to read in French.)

Comment author: lukeprog 10 March 2011 02:28:34AM 3 points [-]

Subject: Meta-ethics

Recommendation: Miller, An Introduction to Contemporary MetaEthics

Reason: Jacobs' The Dimensions of Moral Theory is shorter and easier, for beginners, but it doesn't explain contemporary debates hardly at all. Miller's books is more comprehensive, precise, and contemporary, and even includes some original arguments (the section on Railton is particularly good). I'd like to see an updated third edition, but the 2nd edition from 2003 is still the best thing out there for an overview of meta-ethics. Smith's Ethics and the A Priori is pretty good, but of course it's the opinion of just one philosopher's views, and not good for an overview.

Comment author: alexflint 27 March 2011 10:42:58PM 2 points [-]

Subject: Automated Theorem Proving

Recommendation: Harrison, Handbook of Practical Logic and Automated Reasoning

Reason: Afraid I'm going to break the rules here, I haven't read any other books on the subject but as there's nothing posted here on ATPs I thought this might be useful to someone. The book is an excellent introductory text for someone who has a CS background but not in logic, and who wants to learn about theorem provers for from a practical perspective.

Comment author: Fhyve 31 March 2011 07:27:24PM *  2 points [-]

Recommendation requests: Intro to calculus. I know about derivatives and I can use them and I sort of understand integrals but my knowledge is very fragmented. For instance, I don't know what half of the notation is supposed to actually represent. Also, I want strategies for solving problems rather than being given a bunch of (apparently) unrelated tools and told to just figure it out.... yea, I didn't have a good math teacher

Set theory and other discrete mathematics.

Psychology.

Something or other on the scientific method (how to design experiments)

Biology. General, human, micro, intro or advanced... Just trying to make the list more comprehensive

Chemistry. See above.

Physics. There are already some here but I want more topics (thermodynamics is the first that comes to mind).

In recommendations, I would suggest another criteria be added related to learning type. Some books are being praised for their concreteness and others for their topical comprehensiveness and others for their pedagogical comprehensiveness (addresses most common misconceptions etc.) and other sometimes mutually exclusive traits. Just a way of systematizing this and making it easier for people to get the type of book that they are looking for.

Edit: Another topic: writing. I have read elements of style but I haven't read anything else on the subject. I would like to see how it compares to other (newer?) books.

Comment author: Mimi 19 March 2012 02:12:34AM 1 point [-]

Re: how to design experiments:

Look into statistics. Most experiments have a statistical or hidden statistical basis.

See my suggestions above for calculus.

Comment author: jsalvatier 28 April 2011 10:02:26PM 1 point [-]

I'd like to request a book on Mathematical Economics that teaches you the basics of building and solving utility based microeconomic models (without strategic behavior).

Comment author: badger 28 April 2011 10:27:15PM 1 point [-]

Could you clarify what you are looking for? When I think of mathematical micro models without strategic behavior, my mind goes to general equilibrium models with a continuum of agents. Your use of 'building' suggests you are thinking of something else though.

Comment author: jsalvatier 28 April 2011 10:49:49PM 0 points [-]

That actually sounds like exactly what I want. Can you clarify why 'building' indicates otherwise? I meant 'building' as in 'constructing'.

Comment author: badger 29 April 2011 01:08:25PM 2 points [-]

Since most economists think the Arrow-Debreu model is essentially synonymous with general equilibrium, it just seems odd to talk about building models. If you are thinking of 'model' as a description of a particular economy rather than as a general framework, there are books on computable general equilibrium, but I can't give any particular recommendations.

If you are looking for standard GE theory, look at Existence and Optimality of General Equilibrium by Aliprantis, Burkinshaw, and Brown. It is currently very cheap used on Amazon. There is also a companion book with all the end-of-chapter problems and solutions.

I think I was projecting my skepticism of GE models onto you, assuming that couldn't be what you are really asking for. I'm not sure what theorems about complete-market economies tell us about the real world. There are GE models with incomplete markets, but they involve differential topology beyond my grasp.

Comment author: jsalvatier 29 April 2011 03:21:35PM 0 points [-]

OK, I guess I had in mind something significantly simpler. I am trying to build a model for gaining and sharing understanding. Therefore, I require analytic solutions or another way of characterizing the behavior of the model.

Here's the problem I am trying to model. I want to model a multiple period monetary economy with money treated as a good and couple of other goods and monetary trade only. I am trying to model a minimal interesting model of this sort, so I don't fundamentally care how many agents or other goods there are. I guess the model will probably have two representative agents, and two goods. My model should be 'general equilibrium' in the sense that it is modeling the whole economy, but obviously doesn't need to have remotely complete markets. This seems like it should be possible to do without getting into anything especially fancy, but perhaps I misunderstand.

Do you have any advice?

Comment author: badger 30 April 2011 02:23:16AM 2 points [-]

Alright, hopefully I can give useful recommendations by this point...

Varian's Microeconomic Analysis is probably the best to learn the basics of consumer theory and GE analysis. Since these models don't have any frictions, there isn't any role for money. If you are interested in monetary models, try looking through Kiyotaki and Wright's On Money as a Medium of Exchange or Shapley and Shubik's Trade Using One Commodity as a Means of Payment. These are relatively accessible micro-founded models that should give you an idea of where to head, even if they don't make complete sense now. I don't think models like these have percolated into any textbooks yet.

Comment author: jsalvatier 30 April 2011 10:12:26PM 0 points [-]

OK, thanks! Those are all helpful suggestions.

Comment author: Barry_Cotter 28 April 2011 11:11:52PM 2 points [-]

Fundamental Methods of Mathematical Economics by Alpha C. Chiang is a sufficient basis for entering a graduate programme in Economics. Mathematics for Economists by Carl P. Simon and Lawrence Blume is a higher level book. For miroeconomics as such you probably want to start with Intermediate Microeconomics by Hal Varian, and if you need more you can go to Microeconomic Analysis by same. David D. Friedman's Price Theory is absolutely fine and on his website, free as well.

Comment author: jsalvatier 29 April 2011 12:22:34AM 0 points [-]

Oh good, I've already read Varian, and Chiang was what I was starting to look at.

Comment author: thomblake 09 May 2011 10:16:27PM *  0 points [-]

I should mention that on "machine ethics", "Moral Machines" is not exactly a textbook but it is currently the best source for a view of the entire field. I do not have other books to compare it to because at the moment they do not exist.

CORRECTION: The Andersons' Machine Ethics has been released, so I'll review that and update this.

Comment author: sriku 10 May 2011 02:01:53AM *  7 points [-]

Subject: Basic mathematical physics

Recommendation: Bamberg and Sternberg's A Course in Mathematics for Students of Physics. (two volumes)

Reason: It is difficult to compare this book with other text books since it is extremely accessible, going all the way from 2D linear algebra to exterior calculus/differential geometry, covering electrodynamics, topology and thermodynamics. There is potential for insights into electrodynamics even compared to Feynman's lectures (which I've slurped) or Griffith's. For ex: treating circuit theory and Maxwell's equations as the same mathematical thing. The treatment of exterior calculus is more accessible than the only other treatment I've read which is in Misner Thorne Wheeler's Gravitation.

Comment author: sriku 10 May 2011 02:09:48AM 0 points [-]

I must add that I kept both volumes with me under continuous reborrowal from the univ library for an entire year during my undergrad! Sad and glad that nobody else wanted it :)

Comment author: lukeprog 17 May 2011 06:39:35PM 0 points [-]

Thanks for this! I can't add it to the list because the comparison examples don't quite fit the bill. Though I understand this may be because there simply are no comparisons. If you think of more/better comparisons, please add them so I can reconsider adding it to the list above.

Comment author: Zetetic 15 May 2011 12:36:28AM 9 points [-]

Subject: Problem Solving

Recommendation: Street-Fighting Mathematics The Art of Educated Guessing and Opportunistic Problem Solving

Reason: So, it has come to my attention that there is a freely available .pdf for the textbook for the MIT course Street Fighting Mathematics. It can be found here. I have only been reading it for a short while, but I would classify this text as something along the lines of 'x-rationality for mathematics'. Considerations such as minimizing the number of steps to solution minimizes the chance for error are taken into account, which makes it very awesome.

in any event, I feel that this should be added to the list, maybe under problem solving? I'm not totally clear about that, it seems to be in a class of its own.

Comment author: lukeprog 17 May 2011 06:40:26PM 2 points [-]

If you come up with relevant comparison volumes, let me know!

Comment author: Zetetic 17 May 2011 06:57:39PM *  1 point [-]

Well, they aren't necessarily comparison volumes, but the author suggested that the book should be used as a compliment to the following:

How to Solve It, Mathematics and Plausible Reasoning, Vol. II, The Art and Craft of Problem Solving

He implies that his book is more rough and ready for applications, but those books are more geared towards solving clearly stated problems in, say, a competition setting.

I would add Putnam and Beyond to the list, classifying it as advanced competition style problem solving (some of the stuff in that book is pretty tough).

Comment author: lukeprog 17 May 2011 07:02:56PM 0 points [-]

Have you read any of those? If so, what did you think of them in comparison to 'Street-Fighting Mathematics'?

Comment author: Zetetic 17 May 2011 07:37:46PM *  1 point [-]

I have only read/skimmed through/worked a few problems out of Putnam and Beyond. I can attest to its advanced level (compared to other problem solving books, I have looked at a few before and found that they were geared more towards high school level subject matter; you won't find any actually advanced [read; grad level] topics in it) and systematic presentation, but that is about it. Its problems are mainly chosen from actual math competitions, and it seems to present a useful bag of tricks via well thought out examples and explanations. I am currently working through it and have a ways to go.

I've heard How to Solve It mentioned a number of times, but I've never really looked into it. I can't really say anything about the other books beyond what the author said about them.

Comment author: [deleted] 17 May 2011 07:04:31PM 5 points [-]

Seemingly relevant comparison volumes:

Numbers Rule Your World: The Hidden Influence of Probabilities and Statistics on Everything You Do

Back-of-the-Envelope Physics

How Many Licks? Or, How to Estimate Damn Near Anything

Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin

Also, the books below are listed as related resources in another class on approximation in science & engineering by the author of the Street-Fighting textbook on OCW, so they may be relevant for comparison, too, or at least interesting.

Engel, Arthur. Problem-solving Strategies. New York, NY: Springer, 1999. ISBN: 9780387982199.

Schmid-Nielsen, Knut. Scaling: Why is Animal Size So Important? New York, NY: Cambridge University Press, 1984. ISBN: 9780521319874.

Vogel, Steven. Life in Moving Fluids. 2nd rev. ed. Princeton, NJ: Princeton University Press, 1996. ISBN: 9780691026169.

Vogel, Steven. Comparative Biomechanics: Life's Physical World. Princeton, NJ: Princeton University Press, 2003. ISBN: 9780691112978.

Pólya, George. Induction and Analogy in Mathematics. Vol. 1, Mathematics and Plausible Reasoning. 1954. Reprint, Princeton, NJ: Princeton University Press, 1990. ISBN: 9780691025094.

Comment author: lukeprog 17 May 2011 08:40:34PM 0 points [-]

Great list, thanks!

Comment author: badger 26 May 2011 02:29:46AM *  8 points [-]

Subject: Introductory Decision Making/Heuristics and Biases

Recommendation: Judgment in Managerial Decision Making by Max Bazerman and Don Moore.

This book wins points by being comprehensive, including numerous exercises to demonstrate biases to the reader, and really getting to the point. Insights pop out at every page without lots of fluffy prose. The recommendations are also more practical than other books.

Alternatives:

  • Rational Choice in an Uncertain World by Reid Hastie and Robyn Dawes. A good, well-rounded alternative. Its primary weakness is the lack of exercises.
  • Making Better Decisions: Decision Theory in Practice by Itzhak Gilboa. Filled with exercises, this book would be a great supplement to a course on this subject, but it wouldn't stand alone on self-study. This book specializes in probability and quantitative models, so it's not as practical, but if you've read Bazerman and Moore, read this next if you want to see more of the economic/decision theory approach.
  • How to Think Straight about Psychology by Keith Stanovich. Slanted towards what science is and how to perform and evaluate experiments, this is still a decent introduction.
  • Smart Choices by John Hammond, Ralph Keeney, and Howard Raiffa. Not recommended. Few studies cited and few technical insights, if my memory is correct. The book doesn't go far beyond "clarify your problem, your objectives, and the possible alternatives".
Comment author: lukeprog 26 May 2011 10:25:14PM 4 points [-]

Excellent. I also like Baron's Thinking and Deciding.

Comment author: DBreneman 03 June 2011 11:13:31PM 5 points [-]

It's not exactly a textbook series, but I've found the videos at khan academy http://www.khanacademy.org/#browse to be really helpful with getting the basics of a lot of things. The most advanced math it covers is calculus, which will get you a long way, and the language of the videos is always simple and straightforward.

... Guess I need to recommend it against other video series, to keep to the rules here.

I do recommend watching the stanford lecture videos http://www.youtube.com/user/StanfordUniversity?blend=1&ob=5 , but I recommend Khan over them for simplicity's sake on getting the basics. (Then watch stanford for a more complex understanding)

And though it just covers abiogenesis and evolution, cdk007 http://www.youtube.com/user/cdk007?blend=1&ob=5#p/a does have quite a bit of overlap with khan's biology section. But it's a lot more narrow than what khan covers, and pretty much is just there to counter creationists. While that's a pretty good goal, and the videos are good, it's not as good for learning in my opinion.

Comment author: lukeprog 07 July 2011 01:19:20AM 5 points [-]
Comment author: kjmiller 08 October 2011 03:44:01PM *  7 points [-]

Introduction to Neuroscience

Recommendation: Neuroscience:Exploring the Brain by Bear, Connors, Paradiso

Reasons: BC&P is simply much better written, more clear, and intelligible than it's competitors Neuroscience by Dale Purves and Fundamentals of Neural Science by Eric Kandel. Purves covers almost the same ground, but is just not written well, often just listing facts without really attempting to synthesize them and build understanding of theory. Bear is better than Purves in every regard. Kandel is the Bible of the discipline, at 1400 pages it goes into way more depth than either of the others, and way more depth than you need or will be able to understand if you're just starting out. It is quite well-written, but it should be treated more like an encyclopedia than a textbook.

I also can't help recommending Theoretical Neuroscience by Peter Dayan and Larry Abbot, a fantastic introduction to computational neuroscience, Bayesian Brain, a review of the state of the art of baysian modeling of neural systems, and Neuroeconomics by Paul Glimcher, a survey of the state of the art in that field, which is perhaps the most relevant of all of this to LW-type interests. The second two are the only books of their kind, the first has competitors in Computational Explorations in Cognitive Neuroscience by Randall O'Reilly and Fundamentals of Computational Neuroscience by Thomas Trappenberg, but I've not read either in enough depth to make a definitive recommendation.

Comment author: Peacewise 02 November 2011 02:09:51AM *  5 points [-]

World War II.

"A World at Arms" by Gerhard L. Weinberg is my preferred single book textbook (as a reference) on World War II.

It is a suitably weighty volume on WW2, and does well in looking at the war from a global perspective, it's extensive bibliography and notes are outstanding. In comparison with Churchill's "The Second World War" - in it's single volume edition, Weinburg's writing isn't as readable but does tend to be less personal. Churchill on the other hand is quite personal, when reading his tome, it's almost as if he is sitting there having a chat with you. Churchill is quite frank in revealing his thought processes for making decisions, in fact LWer's might particularly enjoy reading Churchills' account for that reason. Weinberg's A World at Arms is better at looking at multiple view points of the war, whereas Churchill tends to present everything from his point of view. "The Politics of War" by David Day is an Australian centric view point of WW2, it stands as an excellent reference from that perspective, but isn't able to provide an overall picture equal to either Weinburg or Churchill.

Comment author: Chris_Cooper 07 February 2012 03:56:12PM 4 points [-]

I'd like to request Best Textbook suggestions for: climate science and/or climate policy.

Chris

Comment author: Karmakaiser 15 February 2012 10:17:08PM *  -1 points [-]

I do not have the expertise to review all the books, but this is a reddit/r/compsci produced list canonical introductory textbooks covering the major branches of computer science.

link

Comment author: magfrump 08 March 2012 06:17:38PM 5 points [-]

For Elliptic Curves:

I recommend Koblitz' "Elliptic Curves and Modular Forms"

It stays more grounded and focused than Silverman's "Arithmetic of Elliptic Curves," and provides much more detail and background, as well as more exercises, than Cassel's "Lectures on Elliptic Curves."

Is this thread still being maintained? There was a recommendation for it to be a wiki page which seems like a great idea; I'd be willing to put the initial page together in a couple weeks if it hasn't been done but I don't think I can commit to maintaining it.

Comment author: Arepo 14 March 2012 12:51:08PM *  7 points [-]

I don’t know how relevant improv is to Less Wrongers, but I find it helpful for everyday social interactions, so:

Primary recommendation: Salinsky & Frances-White’s The Improv Handbook.

Reason It’s one of the only improv books which actually suggests physical strategies for you to try out that might improve your ability rather than referring to concepts that the author has a pet phrase for that they use as a substitute for explaining what it means. Not all of the suggetions worked for me, and they’re based on primarily on anecdotal evidence (plus the selection effect of the authors having run a reasonably successful improv group in the hostile London climate and only then written a book), but I know of no other book that has as constructive an approach. It also has a number of interview sections and similar, which are eminently skippable – only half the book is really worth reading for performance advice, but fortunately the table of contents make it pretty clear which half that is.

I’m recommending it over Keith Johnstone’s ‘Impro’ and ‘Impro for Storytellers’, whose ideas it incorporates, breaks down and structures far better, over Chris Johnston’s ‘The Improvisation Game’, which is an awful mishmash of interviews and turgid academic writing, over Charna Halpern’s ‘Truth in Comedy’, which has quite a different set of ideas but spends more time boasting about how good they are than explaining them, over Jimmy Carrane and Liz Allen’s Improvising Better, which has a few nice tips and is mercifully short, but doesn’t have anything close to a coherent set of principles, ‘The Improvisation Book’, which I haven’t read in depth but seems to be little more than a list of games, and Dan Patterson and Mark Leveson’s ‘Whose Line is It Anyway’, which unsurprisingly is very heavily focused on emulating the restrictive format of the show of the same name.

Secondary recommendation: Mick Napier’s Improvise, which comes from a different school of thought to TIH’s – the same one as ‘Truth in Comedy’.

Reason It's the only one of any of those I’ve mentioned (TIH included) to explicitly suggest scientific reasoning in developing and assessing improv methods. After the author’s initial proclamation to that effect, he doesn’t really communicate how he’s tried to do so, and his advice seems to assume you’re already quite comfortable with being in an unspecified scene with no preset rules (one of the hardest things for an improviser to find himself in, IME), so I wouldn’t recommend it as a beginner’s guide.

Comment author: Karmakaiser 16 March 2012 07:51:43PM 1 point [-]

This will be a study project to me after the semester so thanks for the recommendations.

Comment author: caustic 16 March 2012 09:00:01PM *  1 point [-]

These two books are great for those who want to study Computer Sciense in a breadth-first manner. While each topic is not discussed in great details, the number of covered topics is mind-boggling. From trivial ones such as Sorting and Searching to more esoteric matter like Pricing Algorithms for Financial Derivatives, etc.

Comment author: Mimi 19 March 2012 02:04:24AM *  2 points [-]

Logic:

--mathematical

Enderton, "A mathematical introduction to logic" then Shoenfield's classic "Mathematical logic"

Cori and Lascar, "Mathematical logic: a course with exercise" for exercises for self-study

Manin, "A course in mathematical logic" for additional enrichment

--computational

Van Dalen's "Logic and Structure" and then Fitting, "First Order Logic and Automated theorem proving" to fill in the gaps

--philosophical

From Frege to Goedel: a sourcebook in mathematical logic

additional works by Frege and Cantor in dover reprints or in the original.

"Goedel's Proof" by Nagel

"Goedel, Escher and Bach" by Hofstadter

--modal and fuzzy

Goldblatt, "Logics of Time and Computation" (Introduction to modal logic through temporal logic)

Bergmann, "An introduction to many valued and fuzzy logic"

Calculus:

Apostol, "Calculus" 2 volumes (Still a classic)

Demidovich, "Problems in mathematical analysis" (Classic drill book)

Topology:

Viro, "Elementary Topology Problem Textbook" (Based on a classic course)

Modern Abstract Algebra:

Jacobson, "Basic Algebra" volumes 1 and 2

History of Western Philosophy:

Basic primary sources in western philosophy (Not a textbook!)