Lenny Rachitsky: Amazing. Hamel. Hamel Husain: Yeah, I have them right here. I'm a nerd. Okay, so I'm not as cool as Shreya is. I actually have textbooks, which are my favorite. This one is a very classic one, Machine Learning by Mitchell. Now, it's theoretical, but the thing I like about it is it really drives home the fact that Occam's razor is prevalent not only in science, but also in machine learning and AI. A lot of times the simplest, and also engineering, so a lot of times the simpler approach generalizes better. That's the thing I internalize deeply from that book. I also really like this one. Another textbook. I told you I'm a nerd. This is also a very old one, and this is Norvig algorithms. I really like it because it's just human ingenuity and it's lots of clever useful things in computing.
Now, it's theoretical, but the thing I like about it is it really drives home the fact that Occam's razor is prevalent not only in science, but also in machine learning and AI.