Reinforcement Learning and Deep RL Python Theory and Projects - Training and Testing the Model

Reinforcement Learning and Deep RL Python Theory and Projects - Training and Testing the Model

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The video tutorial covers the implementation of a PPO model using a CNN policy for a car racing game. It explains the setup of the model, including importing necessary libraries and configuring the environment. The tutorial demonstrates how to train the model with a specified number of time steps and evaluates the policy using episodes. It also shows how to render the game to visualize the agent's performance and discusses the results, including rewards and standard deviation.

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OPEN ENDED QUESTION

3 mins • 1 pt

What new insight or understanding did you gain from this video?

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