Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran

Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python About This Book • 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 various state-of-the-art architectures along with math Who This Book Is For 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. What You Will Learn • 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 • Build intelligent agents using the DRQN algorithm to play the Doom game • Teach agents to play the Lunar Lander game using DDPG • Train an agent to win a car racing game using dueling DQN In Detail 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. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence. Style and approach This is a hands-on book designed to further expand your machine learning skills by understanding reinforcement to deep reinforcement learning algorithms with applications in Python.

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.

SKU	Unavailable
ISBN 13	9781788836524
ISBN 10	1788836529
Title	Hands-On Reinforcement Learning with Python
Author	Sudharsan Ravichandiran
Condition	Unavailable
Publisher	Packt Publishing Limited
Year published	2023-04-02
Number of pages	318
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note	Unavailable