Lecture 1: Course Handout and Introduction
Lecture 2: CNN
Lecture 3: RNN
Lecture 4: Attention Mechanism
Lecture 5: Deep Neural Network Optimization
Lecture 6: Self-Supervised Learning
Lecture 7: Transfer Learning and Domain Adaption
Lecture 8: Model Compression
Lecture 9: Literature Read:Efficient Forward Architecture Search
Lecture 10: Distributed Representations
Lecture 11: GANs
Lecture 12: VQ-VAE
Lecture 13: Graph Neural Network