Course DescriptionThis course will cover the basics of deep reinforcement learning with a focus on core algorithms. We will look at standard reinforcement learning methods like Q-learning and policy gradients along with their neural/deep counterparts. We will also cover a number of practical implementation issues like reward scaling and how to deal with large or continuous action spaces.
- TensorFlow 2
- Basic deep learning/neural networks (CNNs, SGD, etc)
- Basic RL (MDPs, value functions, TD, etc).
LecturerDr. Volodymyr Mnih
Research Scientist at DeepMind