Published by Cambridge University Press (edition ), 2008
ISBN 10: 0521614104 ISBN 13: 9780521614108
Language: English
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Published by Cambridge University Press, 2008
ISBN 10: 0521614104 ISBN 13: 9780521614108
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge India, 2014
Language: English
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Add to basketSoft cover. Condition: New. ISBN:9781107439887,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.
Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2008
ISBN 10: 0521614104 ISBN 13: 9780521614108
Language: English
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Published by Cambridge University Press, 2008
ISBN 10: 0521614104 ISBN 13: 9780521614108
Language: English
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Add to basketPaperback. Condition: 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.
Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2014
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, Cambridge, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Paperback. Condition: new. Paperback. Understand algorithms and their design with this revised student-friendly textbook. Unlike other algorithms books, this one is approachable, the methods it explains are straightforward, and the insights it provides are numerous and valuable. Without grinding through lots of formal proof, students will benefit from step-by-step methods for developing algorithms, expert guidance on common pitfalls, and an appreciation of the bigger picture. Revised and updated, this second edition includes a new chapter on machine learning algorithms, and concise key concept summaries at the end of each part for quick reference. Also new to this edition are more than 150 new exercises: selected solutions are included to let students check their progress, while a full solutions manual is available online for instructors. No other text explains complex topics such as loop invariants as clearly, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems. The second edition of this student-friendly textbook now includes over 150 new exercises, key concept summaries and a chapter on machine learning algorithms. Its approachability and clarity make it ideal as both a main course text or as a supplementary book for students who find other books challenging. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press 2023-11-30, 2023
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Pr. Feb 2024, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -'The second edition of this student-friendly textbook now includes over 150 new exercises, key concept summaries and a chapter on machine learning algorithms. Its approachability and clarity make it ideal as both a main course text or as a supplementary book for students who find other books challenging'-- 500 pp. Englisch.
Published by Cambridge University Press, 2008
ISBN 10: 0521614104 ISBN 13: 9780521614108
Language: English
Seller: Anybook.com, Lincoln, United Kingdom
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Add to basketCondition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:9780521614108.
Published by Cambridge University Press, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
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Published by Cambridge University Press, GB, 2024
ISBN 10: 1009302132 ISBN 13: 9781009302135
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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Add to basketPaperback. Condition: New. Understand algorithms and their design with this revised student-friendly textbook. Unlike other algorithms books, this one is approachable, the methods it explains are straightforward, and the insights it provides are numerous and valuable. Without grinding through lots of formal proof, students will benefit from step-by-step methods for developing algorithms, expert guidance on common pitfalls, and an appreciation of the bigger picture. Revised and updated, this second edition includes a new chapter on machine learning algorithms, and concise key concept summaries at the end of each part for quick reference. Also new to this edition are more than 150 new exercises: selected solutions are included to let students check their progress, while a full solutions manual is available online for instructors. No other text explains complex topics such as loop invariants as clearly, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.