Deep Learning Reading List¶
There is a lot written online about deep learning and AI. Ignoring the fluff and product-hype articles, you’re left with a huge resource for learning the technical side of the field. I won’t claim to have read everything out there, but here are some of the most useful things that I have found. The purpose of this list is not to be a definitive curriculum, but to recommend some of the high-quality educational material that’s out there. If there is an article that you think belongs on this list send me an email.
Edit (June 2024)
This post is from 2016! I've revamped this blog, but kept a few posts from that era, which was a period of intense technical learning and exploration that I look back on fondly.
Education sharing in specialist fields is really cool and we should consider ourselves lucky to have it. My career so far has been based on the fact that anyone with math literacy can self-educate their way through tech.
Adrej Karpathy's blog especially his articles on recurrent neural networks and reinforcement learning. He's a fantastic communicator and educator and he also wrote the classic example of a RNN.
Chris Olah's blog, his article on LSTM explains the difficult to explain.
I use tensorflow, google's deep learning python package. It is well documented and if I can teach it to myself in my spare time so can you.