Deep Learning 2 is a course covering advanced topics and techniques in deep learning. ML 1 and 2 are both recommended prerequisites for this course, you will be expected to be very comfortable with...
Deep Learning 2 is a course covering advanced topics and techniques in deep learning. ML 1 and 2 are both recommended prerequisites for this course, you will be expected to be very comfortable with the basics of neural networks. There will be no review of deep learning, so please make sure that you are familiar with the basics of neural networks before attending lectures if it has been some time since your last ML course. Lectures will cover the following topics:
- Representation Learning
- Attention
- Density Estimation
- Generative Models
- Graph Neural Networks
- Equivariant Neural Networks
- Neural Ordinary Differential Equations
- Deep Reinforcement Learning
- Advanced Explainable AI
