Term 2 (January - April), 2023
Lecture:
Please visit Blackboard for the latest video recording if it is not updated in time.
| Lecture | Description | Course Materials | |
|---|---|---|---|
| Introduction |
[slide] | ||
| 1 | Machine Learning Basics | [slide] | |
| 2 | Multi-Layer Perceptron |
[slide] (updated on Feb 12) | |
| 3 | Convolutional Neural Networks |
[slide] (updated on Feb 15) | |
| 4 | Network Architectures for Image Understanding | [slide] (updated on Feb 21) | |
| 5 | Optimization of Deep Neural Networks | [slide] (updated on March 22) | |
| 9 | Object Detection | [slide] (updated on March 22) | |
| 6 | Recurrent Neural Network | [slide] (updated on Mar 22) | |
| 7 | Attention and Transformer | [slide] (updated on April 3) | |
| 8 | Semantic Segmentation | [slide] (updated on Mar 22) | |
| 8 | Large Language Model | [slide] (updated on April 11) | |
| 8 | Variational Autoencoder | [slide] (updated on April 11) | |
| 9 | Introduction to MMLab | [slide] (updated on April 12) | |
| 9 | Diffusion Models | [slide] (updated on April 19) | |