Deep Q Learning from Paper to Code

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  • Deep Q Learning from Paper to Code

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Intermediate

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Deep Q Learning

47 Lessons

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Deep Q Learning from Paper to Code

Course Introduction

3 Lessons

In this lesson, we'll cover the skills you will learn in this course.

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In this lesson, we'll cover the prerequisites for this course.

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In this lesson, we'll cover some basic strategies for success in this course.

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Fundamentals of Reinforcement Learning

6 Lessons

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In this lesson we cover the fundamentals behind the interplay between an agent and its environment. This leads into the mathematical machinery of deep reinforcement learning.

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Human Level Control Through Deep Reinforcement Learning

14 Lessons

Deep Reinforcement Learning with Double Q Learning

2 Lessons

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Dueling Network Architectures for Deep Reinforcement Learning

4 Lessons

Improving Our Solutions

3 Lessons

Wrapping Up

1 Lesson

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About the teacher

phil

In 2012 I received my PhD in experimental condensed matter physics from West Virginia University. Following that I was a dry etch process engineer for Intel Corporation, where I leveraged big data to make essential process improvements for mission critical products. After leaving Intel in 2015, I have worked as a contract and freelance deep learning and artificial intelligence engineer.

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