Python Reinforcement Learning: Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow
Language: English
Published by Packt Publishing Limited, 2019
- Softcover
- Used
Seller: World of Books Inc, Montgomery, IL, U.S.A.World of Books Inc
AbeBooks seller since March 23, 2026
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Reinforcement learning and deep reinforcement learning are the trending and most promising branches of artificial intelligence. This Learning Path will enable you to master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms and their limitations.
Seller Inventory # CIN1838649778VG
- Title
- Python Reinforcement Learning: Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow
- Author
- Sudharsan Ravichandiran
- Publisher
- Packt Publishing Limited
- Publication year
- 2019
- Condition
- Very Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1838649778
- ISBN 13
- 9781838649777
Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries
Key Features:
- Your entry point into the world of artificial intelligence using the power of Python
- An example-rich guide to master various RL and DRL algorithms
- Explore the power of modern Python libraries to gain confidence in building self-trained applications
Book Description:
Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.
The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL.
By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems.
This Learning Path includes content from the following Packt products:
- Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran
- Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani
What You Will Learn:
- Train an agent to walk using OpenAI Gym and TensorFlow
- Solve multi-armed-bandit problems using various algorithms
- Build intelligent agents using the DRQN algorithm to play the Doom game
- Teach your agent to play Connect4 using AlphaGo Zero
- Defeat Atari arcade games using the value iteration method
- Discover how to deal with discrete and continuous action spaces in various environments
Who this book is for:
If you're an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected.
"Synopsis" may belong to another edition of this title.
About the Author
Sean Saito is the youngest ever Machine Learning Developer at SAP and the first bachelor hired for the position. He currently researches and develops machine learning algorithms that automate financial processes. He graduated from Yale-NUS College in 2017 with a Bachelor of Science degree (with Honours), where he explored unsupervised feature extraction for his thesis. Having a profound interest in hackathons, Sean represented Singapore during Data Science Game 2016, the largest student data science competition. Before attending university in Singapore, Sean grew up in Tokyo, Los Angeles, and Boston.
Rajalingappaa Shanmugamani is currently working as an Engineering Manager for a Deep learning team at Kairos. Previously, he worked as a Senior Machine Learning Developer at SAP, Singapore and worked at various startups in developing machine learning products. He has a Masters from Indian Institute of TechnologyMadras. He has published articles in peer-reviewed journals and conferences and submitted applications for several patents in the area of machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.
"About the title" may belong to another edition of this title.
World of Books Inc
Montgomery, IL, U.S.A.
AbeBooks seller since March 23, 2026
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