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下载方式，关注上面的公众号名片并后台回复： 20240107 Table of contents Chapter 1 - Introduction Chapter 2 - Supervised learning Chapter 3 - Shallow neural networks Chapter 4 - Deep neural networks Chapter 5 - Loss functions Chapter 6 - Training models Chapter 7 - Gradients and initialization Chapter 8 - Measuring performance Chapter 9 - Regularization Chapter 10 - Convolutional networks Chapter 11 - Residual networks Chapter 12 - Transformers Chapter 13 - Graph neural networks Chapter 14 - Unsupervised learning Chapter 15 - Generative adversarial networks Chapter 16 - Normalizing flows Chapter 17 - Variational auto-encoders Chapter 18 - Diffusion models Chapter 19 - Deep reinforcement learning Chapter 20 - Why does deep learning work?
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