Reinforcement Learning and Deep RL Python Theory and Projects - Removing Errors Final Structure Implementation - 3

Reinforcement Learning and Deep RL Python Theory and Projects - Removing Errors Final Structure Implementation - 3

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Information Technology (IT), Architecture

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Hard

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The video tutorial covers the implementation of a deep Q-learning network from scratch. It begins with setting up the environment manager and episode duration tracking. The instructor then attempts to run the Q value class, encountering and debugging several errors. The session continues with plotting results and analyzing moving averages. Finally, the instructor concludes by discussing the potential for using built-in libraries for similar tasks in future modules.

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

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

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