This is the exercise solution video on Perceptron.
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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 Perceptron.
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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 foundation for...

This video explains about the implementation of the neural network class.
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This clip is from the chapter "Deep RL DQN" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on...

This video explains how to load the data.<br<br/>/>

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

This video demonstrates the initializing of the classes.<br<br/>/>

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

This is the first of the three-part video that explains implementing Q-Learning.
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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...

This is the second of the three-part video that explains implementing Q-Learning.
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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...

This is the third of the four-part video that explains implementing Frozen Lake.
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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...

This video demonstrates the initialization of hyperparameters.<br<br/>/>

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

This video demonstrates how to get state.<br<br/>/>

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

This is the second of the three-part video on the final structure implementation.
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This clip is from the chapter "Deep RL DQN" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section...

This video explains how to extract tensors.<br<br/>/>

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

This video explains the implementation of Epsilon Greedy Strategy.<br<br/>/>

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

This video explains about Epsilon.
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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...

This video explains the steps of the DQN algorithm.<br<br/>/>

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

This is an exercise solution video that explains why activation function is required.
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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...