Lingua: Inglese
Editore: Springer (edition Third Edition 2021), 2021
ISBN 10: 3030819345 ISBN 13: 9783030819347
Da: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condizione: Very Good. Third Edition 2021. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Condizione: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2021.
hardcover. Condizione: Very Good.
EUR 42,04
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Aggiungi al carrellohardcover. Condizione: Very Good. An Introduction to Machine Learning This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
EUR 42,04
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Aggiungi al carrellohardcover. Condizione: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
EUR 58,23
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Aggiungi al carrelloCondizione: new.
Condizione: New.
Condizione: New. 3rd ed. 2021 Edition NO-PA16APR2015-KAP.
EUR 62,14
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Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030819345 ISBN 13: 9783030819347
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 61,07
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Hardcover. Condizione: new. New Copy. Customer Service Guaranteed.
EUR 65,47
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Aggiungi al carrelloHardcover. Condizione: Brand New. 3rd edition. 458 pages. 9.75x6.50x1.25 inches. In Stock.
Condizione: As New. Unread book in perfect condition.
EUR 53,49
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EUR 67,35
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EUR 72,67
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Da: UK BOOKS STORE, London, LONDO, Regno Unito
EUR 113,98
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Aggiungi al carrelloHardcover. Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 3rd edition. 458 pages. 9.75x6.50x1.25 inches. In Stock.
EUR 69,54
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications.The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes.