It’s summer. I’m done with my first semester of SE, so let’s talk about ML books that we’re currently studying. My college doesn’t offer ML, nor does it offer any good math classes so if you’re beginner like me, you have to study 24/7 and fail at converting formulae to code so many times you get literally fed up with this crap. I’m studying:

1- My friend’s Computational Linguistics dissertation. I’ve known her for along time, and helped her with Python since she wasn’t a programmer. Now she does NLP better than I do. She does research, and I can’t even understand her dissertation. Partly because it’s in Persian. I used to be an English lit student like her, but I hated English lit. I originally wanted to study CS, but I failed the SATs, so I had to apply to English lit if I wanted to go to a good college. But then I said “fuck it!” and dropped out and applied to community college. Such is life in the third world! Anyways…

2- Foundations of Machine learning by MIT Press. It’s such a great book. It has an unhealthy obsession with PAC though.

3- Introduction to Deep Learning by Eugene Charniak: Oh my God I love this book! So simple! So nifty! It’s obvious it’s been typeset by the same person who did Foundations of et al, because they look practically the same. And both have been published by MIT Press, although Charniak teaches at Brown.

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So what are you studying?