| Description |
1 online resource (473 p.) |
| Note |
Description based upon print version of record. |
| Summary |
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. |
| Contents |
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. |
| Subject |
TensorFlow.
|
|
Machine learning.
|
|
Apprentissage automatique. |
|
Machine learning |
| Other Form: |
Print version: Palanisamy, Praveen TensorFlow 2 Reinforcement Learning Cookbook Birmingham : Packt Publishing, Limited,c2021 9781838982546 |
| ISBN |
1838985999 |
|
9781838985998 (electronic bk.) |
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