Sutton and Barto's Reinforcement Learning textbook: http://incompleteideas.net/book/the-book-2nd.html
Elements of Statistical Learning: https://hastie.su.domains/ElemStatLearn/ as well as the more introductory version: https://www.statlearning.com/
Deep Learning textbook: https://www.deeplearningbook.org/
Bayesian Data Analysis: http://www.stat.columbia.edu/~gelman/book/
Evidence-based software engineering and the second half is a self-contained introduction to data analysis; all the code+data.
Fyi, the link to your site is broken for those viewing on greaterwrong.com; it's interpreting "--a" as part of the link.
I'm looking for online open-source / generously licensed textbooks, papers or tutorials.
Think of stuff like: http://neuralnetworksanddeeplearning.com/
Why? I'm currently running https://chimu.sh --a collaborative learning platform. Quick explanation: Chimu combines an e-reader with a Stack Overflow-like Q&A forum. As people read, they can view others' questions and ask their own. Demo here (desktop works best).
I need to seed the site with initial content, and I figured LW would be a great place to ask.
With this in mind, what are good online tutorials / textbooks that people here have learned from? Is there any book or paper that you wish that you could discuss with your friends?