This video is on evaluation and testing.
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This clip is from the chapter "Stable Baselines Cartpole Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the Stable...

This video talks about the episode.<br<br/>/>

This clip is from the chapter "Terminologies of RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the terminologies of RL.

This video explains the dry run of the get state.
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This clip is from the chapter "Naive Random Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the Naive Random...

This is an exercise solution video on the Loss function in DNN.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...

This video explains about DNN optimizations.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video explains about the implementation of minibatch gradient descent.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This...

This is an exercise solution video on gradient descent.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the...

This video demonstrates about gradient descent.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video explains about DNN early stopping.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video demonstrates about the DNN activation functions in PyTorch.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section...

This video explains about changing policy architecture.
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This clip is from the chapter "Stable Baselines Cartpole Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...

This video explains about callbacks and early stopping.
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This clip is from the chapter "Stable Baselines Cartpole Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...

This video explains automatic differentiation in PyTorch.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the...

This video demonstrates how the Agent plays the game.
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This clip is from the chapter "RL-Based Q-Learning" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on RL-based...

This video explains the agent.<br<br/>/>

This clip is from the chapter "Terminologies of RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the terminologies of RL.

This is a quiz video on Alpha.<br<br/>/>

This clip is from the chapter "Hyper Parameters and Concepts" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on hyper parameters and concepts.

This is an exercise video on reinforcement learning.
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This clip is from the chapter "Motivation and Applications" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the...

This is a summary video on gradient descent.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video concludes the section.<br<br/>/>

This clip is from the chapter "Naive Random Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the Naive Random solution.

This video explains Maven repositories.<br<br/>/>

This clip is from the chapter "Maven" of the series "DevOps Complete Course".This section focuses on Maven from scratch.

This video provides an introduction to Git.<br<br/>/>

This clip is from the chapter "Git and GitHub" of the series "DevOps Complete Course".This section focuses on Git and GitHub.

This video provides an overview of DevOps and covers who can get the most out of this course.
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This clip is from the chapter "Introduction to the Course" of the series "DevOps Complete Course".This section provides an...

This video shows how to create the first Maven project.<br<br/>/>

This clip is from the chapter "Maven" of the series "DevOps Complete Course".This section focuses on Maven from scratch.

This video explains what PEP8 is and why actually it is needed.<br<br/>/>

This clip is from the chapter "PEP 8 Code Layout" of the series "PEP8 Guidelines: Python Clean Coding".This section explains the PEP8 code layout.