The code library for practicing the textbook Deep Learning.
ref info: https://www.bishopbook.com/
Ch1 The Deep Learning Revolution
Ch2 Probabilities
Ch3 Standard Distributions
Ch4 Single-layer Networks: Regression
Ch5 Single-layer Networks: Classification
Ch6 Deep Neural Networks
Ch7 Gradient Descent
Ch8 Backpropagation
Ch9 Regularization
Ch10 Convolutional Networks
Ch11 Structured Distributions
Ch12 Transformers
Ch13 Graph Neural Networks
Ch14 Sampling
Ch15 Discrete Latent Variables
Ch16 Continuous Latent Variables
Ch17 Generative Adversarial Networks
Ch18 Normalizing Flows
Ch19 Autoencoders