Introductions

• * Deep Learning Book - Part I: Applied Math and Machine Learning Basics

MLPs, Gradient Descent & Backpropagation

• Deep Learning Book - Chapter 6: Deep Feedforward Networks

CNNs

• Deep Learning Book - Chapter 9: Convolutional Networks, Sections 9.1 to 9.5

CNNs (cont.)

• Deep Learning Book - Chapter 9: Convolutional Networks, remaining sections
• 1 of 5 papers (see Mattermost channel to cast votes)

RNNs

• Deep Learning Book - Chapter 10: Sequence Modeling: Recurrent and Recursive Nets, Sections 10.1 to 10.5

RNNs (cont.)

• Deep Learning Book - Chapter 10: Sequence Modeling: Recurrent and Recursive Nets, Sections 10.6, 10.7 and 10.10 to 10.12

Autoencoders

• Deep Learning Book - Chapter 14: Autoencoders

Introspection & Advanced Architectures

• Reading Assignment

Optimization

• Deep Learning Book - Chapter 8: Optimization (except Section 8.6)

Regularization

• Deep Learning Book - Chapter 7: Regularization

Practical Methodology

• Deep Learning Book - Chapter 11: Practical Methodology

Course Project

Attention and Memory

• Reading Assignment

Model Compression & Transfer Learning

• Reading Assignment