TensorFlow 2 Reinforcement Learning Cookbook
This cookbook will help you to gain a solid understanding of deep reinforcement learning (RL) algorithms with the help of concise, easy-to-follow implementations from scratch. You'll learn how to implement these algorithms with minimal code and develop AI applications to solve real-world and business problems using RL.
Offered by
Difficulty Level
Intermediate
Completion Time
15h44m
Language
English
About Book
Who Is This Book For?
The book is for machine learning application developers, AI and applied AI researchers, data scientists, deep learning practitioners, and students with a basic understanding of reinforcement learning concepts who want to build, train, and deploy their own reinforcement learning systems from scratch using TensorFlow 2.x.
TensorFlow 2 Reinforcement Learning Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 15h44m total length
Developing building blocks for Deep RL using TensorFlow 2.x
Implementing value-based, policy gradients and actor-critic Deep RL algorithms
Implementing Advanced Deep RL algorithms
RL in real-world: Building intelligent trading agents
RL in Real-World: Building Stock Trading Agents
RL in real-world: Building intelligent agents to complete your ToDos
Deploying Deep RL Agents to the Cloud
Building cross-platform (web, desktop, mobile) Deep-RL Apps using TensorFlow 2.x
Distributed training and automated production deployment pipeline for Deep RL Apps
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