Description: About this Item The item is a book Paperback The Author Name is Maxim Lapan The Title is Deep Reinforcement Learning Hands-On : Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more Condition New Other Comments Edition Number - 0001. Edition_description - First. Pages Count - 546. Binding type - Perfect. Content Language - English Category - COMPUTERS / Artificial Intelligence / General COMPUTERS / Artificial Intelligence / Natural Language Proce COMPUTERS / Programming / Algorithms Product Description - 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 RL, from the first principles to the latest algorithms Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms Keep up with the very latest industry developments, including AI-driven chatbotsBook DescriptionRecent developments in reinforcement learning RL, combined with deep learning DL, have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. What you will learn Understand the DL context of RL and implement complex DL models Learn the foundation of RL: Markov decision processes Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others Discover how to deal with discrete and continuous action spaces in various environments Defeat Atari arcade games using the value iteration method Create your own OpenAI Gym environment to train a stock trading agent Teach your agent to play Connect4 using AlphaGo Zero Explore the very latest deep RL research on topics including AI-driven chatbotsWho this book is forSome fluency in Python is assumed. Basic deep learning DL approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning RL and requires no background in RL. We Use Stock Images Because we have over 2 million items for sale we have to use stock images, this listing does not include the actual image of the item for sale. The purchase of this specific item is made with the understanding that the image shown in this listing is a stock image and not the actual item for sale. For example: some of our stock images include stickers, labels, price tags, hyper stickers, obi's, promotional messages, signatures and or writing which may not be available in the actual item. When possible we will add details of the items we are selling to help buyers know what is included in the item for sale. The details are provided automatically from our central master database and can sometimes be wrong. Books are released in many editions and variations, such as standard edition, re-issue, not for sale, promotional, special edition, limited edition, and many other editions and versions. The Book you receive could be any of these editions or variations. If you are looking for a specific edition or version please contact us to verify what we are selling. Gift IdeasThis is a great Christmas gift idea. Hours of ServiceWe have many warehouses, some of the warehouses process orders seven days a week, but the Administration Support Staff are located at a head office location, outside of the warehouses, and typically work only Monday to Friday. Location ID 555z iHaveit SKU ID 164100264
Price: 51.47 GBP
Location: GB
End Time: 2024-11-18T07:32:39.000Z
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Fiction/Non-Fiction: Non-Fiction
Genre/Subject: COMPUTERS / Artificial Intelligence / General
Brand: Packt Publishing Limited
Weight: 0.93
Style: NA
Title: Deep Reinforcement Learning Hands-On Apply modern RL methods w
Release Title: Deep Reinforcement Learning Hands-On Apply modern RL methods w
Record Grading: New
Sleeve Grading: New
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Film/TV Title: Deep Reinforcement Learning Hands-On Apply modern RL methods
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Binding Type: Perfect
Item Length: 234.95
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Publisher: Packt Publishing
Publication Year: 2018
Subject: Computer Science
Item Height: 93 mm
Number of Pages: 546 Pages
Language: English
Publication Name: Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Type: Textbook
Author: Maxim Lapan
Item Width: 75 mm
Format: Paperback
