There are many online resources that can be helpful for learning the content of this class. Here are a few. If you find others, please post on Piazza and we can add them here.
- Michael Nielsen’s online book
- Deep Learning textbook by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- Unsupervised Feature Learning and Deep Learning Tutorial from Stanford
- CS231n: Convolutional Neural Networks for Visual Recognition lecture notes by Andrej Karpathy
- CS294: Deep Reinforcement Learning Course on reinforcement learning by Sergey Levine
- Neural Networks Appendix E of Principles of Neural Science, 5th ed. Eds. E. R. Kandel et al. by S. Seung and R. Yuste
Python tutorial: PicScie.
- Part I
- Part II
Extra readings on the history of neural networks and their recent revival: