Isbn: 9781788834247 - deep reinforcement learning hands-on: apply modern rl methods, with deep q-networks, value iteration, policy gradients, trpo, alphago zero and more (31 risultati)

paperback. Condizione: Good.

Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condizione: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Condizione: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condizione: very_good. Item may have minor cosmetic defects marks, wears, cuts, bends, crushes on the cover, spine, pages or dust cover. Shrink wrap, dust covers, or boxed set case may be missing. Item may contain remainder marks on outside edges, which should be noted in Product Details. Item may be missing bundled media.…

Condizione: good. Gently used with light wear to the cover, corners, or spine. Pages are clean and free of writing or highlighting. Binding is tight and fully intact. Dust jacket included with hardcover books. Ships fast in a protective poly mailerâ"Monday through Friday, excluding weekends and holidays.…

Condizione: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

paperback. Condizione: Good. Our good condition books are generally good for reading but not for gifting or collecting. They could have imperfections such as creasing, fanning, inscriptions, margin notes, yellowing, staining on edge or cover or pages, bumps, scuffs, etc etc (sometimes multiple of these). It's a wide category that encompasses anything that isn't almost-new down to anything that is slightly better than poor. We would NOT recommend gifting Good books - these should be considered reading copies. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.…

Condizione: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Condizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Broschiert/Paperback. Condizione: Gut. 523 p. Guter Zustand. Einband mit minimalen Gebrauchsspuren. Seiten sauber. / Good. Cover shows minimal wear. Clean pages. Sprache: Englisch Gewicht in Gramm: 1230.

Condizione: New.

Paperback or Softback. Condizione: New. Deep Reinforcement Learning Hands-On. Book.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: Gut. 546 S. Mit altersbedingten Lager- und Gebrauchsspuren. Seiten und Umschlag ggf. nachgedunkelt. Elk-38B Sprache: Englisch Gewicht in Gramm: 925 Taschenbuch, Maße: 19.05 cm x 3.12 cm x 23.5 cm.

Paperback. Condizione: New. Publisher\'s Note: This edition from 2018 is outdated and not compatible with any of the most recent updates to Python libraries. A new third edition, updated for 2020 with six new chapters that include multi-agent methods, discrete optimization, RL in robotics, and advanced exploration techniques is now available.Key FeaturesExplore deep reinforcement learning (RL), from the first principles to the latest algorithmsEvaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithmsKeep up with the very latest industry developments, including AI-driven chatbotsBook DescriptionDeep 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 learnUnderstand the DL context of RL and implement complex DL modelsLearn the foundation of RL: Markov decision processesEvaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and othersDiscover how to deal with discrete and continuous action spaces in various environmentsDefeat Atari arcade games using the value iteration methodCreate your own OpenAI Gym environment to train a stock trading agentTeach your agent to play Connect4 using AlphaGo ZeroExplore 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.…

Condizione: New. pp. 546.

Condizione: New.

Condizione: New. In English.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New. Publisher\'s Note: This edition from 2018 is outdated and not compatible with any of the most recent updates to Python libraries. A new third edition, updated for 2020 with six new chapters that include multi-agent methods, discrete optimization, RL in robotics, and advanced exploration techniques is now available.Key FeaturesExplore deep reinforcement learning (RL), from the first principles to the latest algorithmsEvaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithmsKeep up with the very latest industry developments, including AI-driven chatbotsBook DescriptionDeep 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 learnUnderstand the DL context of RL and implement complex DL modelsLearn the foundation of RL: Markov decision processesEvaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and othersDiscover how to deal with discrete and continuous action spaces in various environmentsDefeat Atari arcade games using the value iteration methodCreate your own OpenAI Gym environment to train a stock trading agentTeach your agent to play Connect4 using AlphaGo ZeroExplore 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.…

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Print on Demand pp. 546.

Condizione: New. PRINT ON DEMAND pp. 546.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging p.…