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"Introduction to Statistical Learning" - https://www.statlearning.com/ https://www.statlearning.com/ (there's also "Elements of Statistical Learning" which is
by softwaredoug 4y ago
"Introduction to Statistical Learning" - https://www.statlearning.com/ https://www.statlearning.com/
(there's also "Elements of Statistical Learning" which is a more advanced version)
AI: A Modern Approach - https://aima.cs.berkeley.edu/ https://aima.cs.berkeley.edu/
- bjornsing 4y agoThe Elements of Statistical Learning, by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie. I’ve seen it referenced quite a few times and the TOC looks good.
- kevinskii 4y agoI agree. I read the first edition to Intro to Statistical Learning and it went into just the right level of mathematical depth. The authors also have Youtube lectures that accompany the chapters, and these are a great reinforcement of the material.
- jay3ss 4y agoDo you have a link to the YouTube lectures? I'm taking a course and this is one of the books that we're using
- rg111 4y agoISL is a legit good book. Has the correct amount and balance or rigor and application. The explanation, examples, projects, math- all are crisp. As the name suggests, it is only an introduction (unlike CLRS). And it does serve as a great beginners' book giving you proper foundation for the things that you learn and apply in the future. One thing people complain about is it being written in R, but no serious hacker should fear R, as it can be picked up in 30 minutes, and you can implement the ideas in Python. As someone with industry experience in Deep Learning, I will recommend this book. The ML course by Andrew Ng has no parallel, though. One must try and do that course. Not sure about the current iteration, but the classic one (w/ Octabe/MATLAB) was really great.
- ranc1d 4y agoNice I didn't realise they released a 2nd edition this book and also new website too! Thanks for sharing