Dive into reinforcement learning concepts and build applications that can learn and make decisions through trial and error.
Fundamentals of Reinforcement Learning
2
lectures
Understanding Rewards and Policies
Exploration vs. Exploitation
Building RL Models
3
lectures
Implementing Q-Learning
Deep Q-Networks (DQN)
Policy Gradient Methods
Trainer
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Trainer Name
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