Comprehensive introduction to reinforcement learning, covering Markov decision processes, dynamic programming, and more. Taught by leading expert David Silver from DeepMind.
This course provides an in-depth introduction to reinforcement learning, covering topics such as Markov decision processes, dynamic programming, model-free prediction and control, value function approximation, policy gradient methods, and the integration of learning and planning. The course is taught by David Silver, a leading expert in the field of reinforcement learning and a researcher at DeepMind.
This course is highly recommended for anyone interested in reinforcement learning, whether you are a student, a researcher, or a practitioner in the field of artificial intelligence and machine learning. The course provides a solid foundation in reinforcement learning and covers the latest advancements in the field, making it a valuable resource for both beginners and experienced learners.
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