Reinforcement Learning and Deep RL Python Theory and Projects - Callbacks and Early Stopping

The video tutorial covers the evaluation of a model and the implementation of early stopping using callbacks. It explains how to set a reward threshold to stop training when the model reaches a desired performance level. The tutorial also discusses saving the best model during training and evaluates the model's performance at regular intervals. The importance of avoiding overfitting by stopping training at the right time is emphasized.

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