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TensorFlow 2 Reinforcement Learning Cookbook

You're reading from  TensorFlow 2 Reinforcement Learning Cookbook

Product type Book
Published in Jan 2021
Publisher Packt
ISBN-13 9781838982546
Pages 472 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Palanisamy P Palanisamy P
Profile icon Palanisamy P
LinkedIn
Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.
See other products by Palanisamy P

Table of Contents (11) Chapters

Preface 1. Chapter 1: Developing Building Blocks for Deep Reinforcement Learning Using Tensorflow 2.x 2. Chapter 2: Implementing Value-Based, Policy-Based, and Actor-Critic Deep RL Algorithms 3. Chapter 3: Implementing Advanced RL Algorithms 4. Chapter 4: Reinforcement Learning in the Real World – Building Cryptocurrency Trading Agents 5. Chapter 5: Reinforcement Learning in the Real World – Building Stock/Share Trading Agents 6. Chapter 6: Reinforcement Learning in the Real World – Building Intelligent Agents to Complete Your To-Dos 7. Chapter 7: Deploying Deep RL Agents to the Cloud 8. Chapter 8: Distributed Training for Accelerated Development of Deep RL Agents 9. Chapter 9: Deploying Deep RL Agents on Multiple Platforms 10. Other Books You May Enjoy

Packaging RL agents for deployment – a trading bot

This is one of the crucial recipes of this chapter, where we will be discussing how to package the agent so that we can deploy on the cloud (next recipe!) as a service. We will be implementing a script that takes our trained agent models and exposes the act method as a RESTful service. We will then package the agent and the API script into a Docker container that is ready to be deployed to the cloud! By the end of this recipe, you will have built a deployment-ready Docker container with your trained RL agent that is ready to create and offer your Agent/Bot-as-a-Service!

Let’s jump into the details.

Getting ready

To complete this recipe, you will first need to activate the tf2rl-cookbook Python/conda virtual environment. Make sure to update the environment to match the latest conda environment specification file (tfrl-cookbook.yml) in the cookbook’s code repository. If the following import statements run...

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Authors (1)

Profile icon Palanisamy P
LinkedIn
Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.
See other products by Palanisamy P

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