Book Image

Reinforcement Learning with TensorFlow

By : Sayon Dutta
Book Image

Reinforcement Learning with TensorFlow

By: Sayon Dutta

Overview of this book

Reinforcement learning (RL) allows you to develop smart, quick and self-learning systems in your business surroundings. It's an effective method for training learning agents and solving a variety of problems in Artificial Intelligence - from games, self-driving cars and robots, to enterprise applications such as data center energy saving (cooling data centers) and smart warehousing solutions. The book covers major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You'll also be introduced to the concept of reinforcement learning, its advantages and the reasons why it's gaining so much popularity. You'll explore MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, and temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have gained a firm understanding of what reinforcement learning is and understand how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym.
Table of Contents (21 chapters)
Title Page
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Appendix 2. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Deep Learning with TensorFlow - Second Edition Giancarlo Zaccone, Md. Rezaul Karim

ISBN: 978-1-78883-110-9


  • Apply deep machine intelligence and GPU computing with TensorFlow v1.7
  • Access public datasets and use TensorFlow to load, process, and transform the data
  • Discover how to use the high-level TensorFlow API to build more powerful applications
  • Use deep learning for scalable object detection and mobile computing
  • Train machines quickly to learn from data by exploring reinforcement learning techniques
  • Explore active areas of deep learning research and applications

Predictive Analytics with TensorFlow Md. Rezaul Karim

ISBN: 978-1-78839-892-3

  • Get a solid and theoretical understanding of linear algebra, statistics, and probability for predictive modeling
  • Develop predictive models using classification, regression, and clustering algorithms
  • Develop predictive models for NLP
  • Learn how to use reinforcement learning for predictive analytics
  • Factorization Machines for advanced recommendation systems
  • Get a hands-on understanding of deep learning architectures for advanced predictive analytics
  • Learn how to use deep Neural Networks for predictive analytics
  • See how to use recurrent Neural Networks for predictive analytics
  • Convolutional Neural Networks for emotion recognition, image classification, and sentiment analysis