Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Deep Learning with TensorFlow

You're reading from   Deep Learning with TensorFlow Explore neural networks and build intelligent systems with Python

Arrow left icon
Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788831109
Length 484 pages
Edition 2nd Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Giancarlo Zaccone Giancarlo Zaccone
Author Profile Icon Giancarlo Zaccone
Giancarlo Zaccone
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with Deep Learning 2. A First Look at TensorFlow FREE CHAPTER 3. Feed-Forward Neural Networks with TensorFlow 4. Convolutional Neural Networks 5. Optimizing TensorFlow Autoencoders 6. Recurrent Neural Networks 7. Heterogeneous and Distributed Computing 8. Advanced TensorFlow Programming 9. Recommendation Systems Using Factorization Machines 10. Reinforcement Learning Other Books You May Enjoy Index

OpenAI Gym


OpenAI Gym is an open source Python framework developed by OpenAI, a non-profit AI research company, as a toolkit for developing and evaluating RL algorithms. It gives us a set of test problems, known as environments, that we can write RL algorithms to solve. This enables us to dedicate more of our time to implementing and improving the learning algorithm instead of spending a lot of time simulating the environment. In addition, it provides a medium for people to compare and review the algorithms of others.

OpenAI environments

OpenAI Gym has a collection of environments. At the time of writing this book, the following environments are available:

  • Classic control and toy text: Small-scale tasks from the RL literature.

  • Algorithmic: Performs computations such as adding multi-digit numbers and reversing sequences. Most of these tasks require memory, and their difficulty can be changed by varying the sequence length.

  • Atari: Classic Atari games, with screen images or RAM as input, using...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image