Hands-On Reinforcement Learning with Python

Download or Read eBook Hands-On Reinforcement Learning with Python PDF written by Sudharsan Ravichandiran and published by Packt Publishing Ltd. This book was released on 2018-06-28 with total page 309 pages. Available in PDF, EPUB and Kindle.
Hands-On Reinforcement Learning with Python
Author :
Publisher : Packt Publishing Ltd
Total Pages : 309
Release :
ISBN-10 : 9781788836913
ISBN-13 : 178883691X
Rating : 4/5 (13 Downloads)

Book Synopsis Hands-On Reinforcement Learning with Python by : Sudharsan Ravichandiran

Book excerpt: A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python 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 various state-of-the-art architectures along with math Book Description 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. 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 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.


Hands-On Reinforcement Learning with Python Related Books

Hands-On Reinforcement Learning with Python
Language: en
Pages: 309
Authors: Sudharsan Ravichandiran
Categories: Computers
Type: BOOK - Published: 2018-06-28 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the world of artificial
Hands-On Reinforcement Learning for Games
Language: en
Pages: 420
Authors: Micheal Lanham
Categories: Computers
Type: BOOK - Published: 2020-01-03 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key FeaturesGet to
Hands-On Q-Learning with Python
Language: en
Pages: 200
Authors: Nazia Habib
Categories: Mathematics
Type: BOOK - Published: 2019-04-19 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Leverage the power of reward-based training for your deep learning models with Python Key FeaturesUnderstand Q-learning algorithms to train neural networks usin
Deep Reinforcement Learning Hands-On
Language: en
Pages: 547
Authors: Maxim Lapan
Categories: Computers
Type: BOOK - Published: 2018-06-21 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (R
Python Reinforcement Learning Projects
Language: en
Pages: 287
Authors: Sean Saito
Categories: Computers
Type: BOOK - Published: 2018-09-29 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key FeaturesImplement Q-learning and Markov models wit