Delve into the world of reinforcement studying algorithms and apply them to totally different use-cases by way of Python. This guide covers vital matters akin to coverage gradients and Q studying, and makes use of frameworks akin to Tensorflow, Keras, and OpenAI Fitness center.
Utilized Reinforcement Studying with Python introduces you to the speculation behind reinforcement studying (RL) algorithms and the code that will likely be used to implement them. You’ll take a guided tour by options of OpenAI Fitness center, from using commonplace libraries to creating your individual environments, then uncover tips on how to body reinforcement studying issues so you may analysis, develop, and deploy RL-based options.
What You’ll Be taught
- Implement reinforcement studying with Python
- Work with AI frameworks akin to OpenAI Fitness center, Tensorflow, and Keras
- Deploy and prepare reinforcement studying–based mostly options by way of cloud assets
- Apply sensible functions of reinforcement studying
Who This Ebook Is For
Information scientists, machine studying engineers and software program engineers accustomed to machine studying and deep studying ideas.
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