Lecture Handouts

Here are online lecture notes used in class and they will be updated until the day the lecture is given. If you must print out a section of slides, try to print double-sided. Thanks for saving paper!

Some materials of this course come from the slides in https://d2l.ai, and http://introtodeeplearning.com/.  

 

Topic	Title
1	Course introduction Deep Learning Preliminaries	Matrix calculus http://www.matrixcalculus.org/ [derivatives notes]
2	Introduction to Deep learning Multilayer Perceptron	A Neural Network Playground
3	Convolutional Neural Networks
4	Recurrent Neural Networks
5	Neural Networks and Backpropagation
6	Advanced CNNs for Image Classification
7	Advanced CNNs for Object Detection
8	Advanced Networks for Dense Prediction
9	Transformer
10	Graph Neural Networks (GNN)
-	Midterm Arrangement Midterm Example Midterm Solution COMP4901J Midterm Sample COMP4901J Midterm Solution
11	Video Models
12	Self-supervised Learning
13	Generative Models	GANs, Diffusion Models
14	Robot Learning
15	Generalization, Style Transfer
16	Deep 3D Vision
17	Normalizing Flow and Diffusion Models