Introduction Deep Learning Logical by Skansi Sandro (13 results)

Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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paperback. Condition: 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.

Language: English
Published by Springer International Publishing AG, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Condition: 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.

Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Condition: New. In English.

Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Language: English
Published by Springer-Verlag New York Inc, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 191 pages. 9.25x6.00x0.75 inches. In Stock.

Language: English
Published by Springer, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Introduction to Deep Learning | From Logical Calculus to Artificial Intelligence | Sandro Skansi | Taschenbuch | Undergraduate Topics in Computer Science | xiii | Englisch | 2018 | Springer | EAN 9783319730035 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Language: English
Published by Springer 2018-02, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
- Print on Demand
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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PF. Condition: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Language: English
Published by Palgrave Macmillan, 2018
Series: Book 64 of 99 - Undergraduate Topics in Computer Science
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website.Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism.This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.…