Chapter 5 Machine Learning Basics

Chapter 6 Deep Feedforward Networks

Chapter 7 Regularization for Deep Learning

Chapter 8 Optimization for Training Deep Models

Chapter 9 Convolutional Network

Chapter 10 Sequence Modeling: Recurrent and Recursive Nets

Chapter 11 Practical Methodology

Chapter 12 Application

Chapter 13 Linear Factor Models

Chapter 14 Autoencoders