Recently, I have received many requests about how I learned Neural Networks. Since this is so new that not that many Universities offer a class in it, I thought I should put together a list of learning material I found useful. Hopefully other people will find it useful too.

1. I’m an audio learner and love to listen to people. So Andrew Ng’s Coursera course was good for me. https://www.coursera.org/specializations/deep-learning. Take all four if you have time and try to understand the exercises and not just manipulate the program to get the correct answer. Actually understand the Math behind it.
2. Ian Goodfellow’s books cover the math background you need and he shows you how to apply it. https://www.deeplearningbook.org/. This is a good reference book if you find yourself lost in some concept a paper mentioned. The dreaded, “for obviously reasons, …”
3. If you find you want some statistics background, I read this book, http://www-bcf.usc.edu/~gareth/ISL/. There is another more bible like statistics book, but if I cannot understand it, I’m not going to suggest it to anybody.
4. Cornell University have an open archive for all sciences. And you can find the specific journal articles related to AI, Computer Vision, Speech, and NLP. https://arxiv.org/. It is intimidating in the beginning to read papers, just from the amount of jargons people use. But after you read several it’s not that bad. Otherwise, refer to Ian’s book or just google it.
5. MIT online course videos are good for general background in Math and CS. Again, I prefer listening to lectures much more than reading books. I just fall asleep too much.
6. Stanford class notes is where I started: http://cs231n.stanford.edu/. Image recognition is easier to understand but hard to master.
7. Grant’s video on youtube has the best visualizations. And they are the best linear algebra video I have ever seen on transformation. You are going to need linear algebra. It speed up your computation by a ton, if nothing else. https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
8. I would say most import of all, find a paper with code and just play with it. You can put code on Google Colab and get free GPU. https://paperswithcode.com/

Secret: Use Twitter to follow the experts in AI. Build it up to specialize in the field you like. e.g. reinforcement learning. I will get you started with some famous names: @geoffreyhinton, @ylecun, @AndrewYNg, and @goodfellow_ian.