Advanced Deep Learning and Reinforcement Learning Advanced Deep Learning and Reinforcement Learning course taught at UCL in partnership with DeepMind Deep Learning 1: Introduction to Machine Learning Based AI [slides] [video] Deep Learning 2: Introduction to TensorFlow [slides] [video] Deep Learning 3: Neural Networks Foundations [slides] [video] Reinforcement Learning 1: Introduction to Reinforcement Learning [slides] [video] Reinforcement Learning 2: Exploration and Exploitation [slides] [video] Reinforcement Learning 3: Markov Decision Processes and Dynamic Programming [slides] [video] Reinforcement Learning 4: Model-Free Prediction and Control [slides] [video] Deep Learning 4: Beyond Image Recognition, End-to-End Learning, Embeddings [slides] [video] Reinforcement Learning 5: Function Approximation and Deep Reinforcement Learning [slides] [video] Reinforcement Learning 6: Policy Gradients and Actor Critics [slides] [video] Deep Learning 5: Optimization for Machine Learning [slides] [video] Reinforcement Learning 7: Planning and Models [slides] [video] Deep Learning 6: Deep Learning for NLP [slides] [video] Reinforcement Learning 8: Advanced Topics in Deep RL [slides] [video] Deep Learning 7. Attention and Memory in Deep Learning [slides] [video] Reinforcement Learning 9: A Brief Tour of Deep RL Agents [slides] [video] Deep Learning 8: Unsupervised learning and generative models [slides] [video] Reinforcement Learning 10: Classic Games Case Study [slides] [video]