P / Praveen TensorFlow 2 Reinforcement Learning Cookbook

Over 50 recipes to help you build, train, and deploy learning agents for real-world applications
1. Auflage 2021
ISBN: 978-1-83898-599-8
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 472 Seiten

No detailed description available for "TensorFlow 2 Reinforcement Learning Cookbook".

Autoren/Hrsg.

P, Palanisamy

Praveen, Palanisamy

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

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

Über Autor(innen)

P Palanisamy:

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.