TensorFlow 2 Reinforcement Learning Cookbook : Over 50 Recipes to Help You Build, Train, and Deploy Learning Agents for Real-World Applications.
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 bu...
| Váldodahkki: | |
|---|---|
| Materiálatiipa: | Licensed eBooks |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
Birmingham :
Packt Publishing, Limited,
2021.
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| Liŋkkat: | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2731480 |
Sisdoallologahallan:
- Table of Contents 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.