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Deep Reinforcement Learning in Python

Timothée Carayol

Principal Machine Learning Engineer, Komment

Chapter 1

An illustration of a Q-network, mapping the state, represented as a globe, to 4 actions corresponding to up, right, down, and left.

Deep Reinforcement Learning in Python

Chapter 2

A collection of illustrations for concepts related to Deep Q learning algorithms: the Q function, epsilon greediness, fixed Q targets, and experience replay.

Deep Reinforcement Learning in Python

Chapter 3

A diagram representing the dynamics of A2C.

Deep Reinforcement Learning in Python

Chapter 4

A Mars rover happily exploring the Mars landscape.

Deep Reinforcement Learning in Python

What next?

A robot looking thoughtful in a lush futuristic scenery

Deep Reinforcement Learning in Python

Well done!

Deep Reinforcement Learning in Python

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