📄 Chapter 1 - Introduction 📄 Chapter 4 - Deep Neural Networks 📄 Chapter 5 - Loss functions 📄 Chapter 6 - Fitting models 📄 Chapter 7 - Gradients and Initialization 📄 Chapter 8 - Measuring performanc 📄 Chapter 9 - Regularization 📄 Chapter 10 - CNNs 📄 Chapter 11 - Residual Networks 📄 Chapter 12 - Transformers 📄 Chapter 13 - Graph Networks 📄 Chapter 14 - Unsupervised Learning 📄 Chapter 16 - Normalizing Flows 📄 Chapter 17 - VAE 📄 Chapter 18 - Diffusion 📄 index 📄 The Programmers Brain