This is the code repository for Hands-On-Reinforcement-Learning-with-Python, published by Packt.
Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.
This book covers the following exciting features:
- Understand the basics of reinforcement learning methods, algorithms, and elements
- Train an agent to walk using OpenAI Gym and Tensorflow
- Understand the Markov Decision Process, Bellman’s optimality, and TD learning
- Solve multi-armed-bandit problems using various algorithms
- Master deep learning algorithms, such as RNN, LSTM, and CNN with applications
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
policy_iteration():
Initialize random policy
for i in no_of_iterations:
Q_value = value_function(random_policy)
new_policy = Maximum state action pair from Q value
Following is what you need for this book: If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book.
With the following software and hardware list you can run all code files present in the book (Chapter 1-15).
| Chapter | Software required | OS required |
|---|---|---|
| 1-12 | anaconda | Ubutnu or mac |
| chrome | Ubutnu or mac |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Sudharsan Ravichandiran is a data scientist, researcher, artificial intelligence enthusiast, and YouTuber (search for Sudharsan reinforcement learning). He completed his bachelors in information technology at Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning, which includes natural language processing and computer vision. He used to be a freelance web developer and designer and has designed award-winning websites. He is an open source contributor and loves answering questions on Stack Overflow.
Click here if you have any feedback or suggestions.