Applied Reinforcement Learning with Python

Book Description:

Delve into the area of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics like policy gradients and Q learning, and utilizes frameworks like Tensorflow, Keras, and OpenAI Gym.

Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through characteristics of OpenAI Gym, from using standard libraries to making your own environments, then discover how to frame reinforcement learning issues so it is possible to explore, develop, and deploy RL-based options.

What You Will Learn

• Implement reinforcement learning with Python
• Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras
• Deploy and instruct reinforcement learning–established alternatives via cloud resources
• Employ practical applications of reinforcement learning

Who This Book Is For

Data scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.

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