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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Very Good. Cover and edges may have some wear.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
hardcover. Condition: New.
-
Machine Learning : A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: New.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: 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.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: Prior Books Ltd, Cheltenham, United Kingdom
Association Member: ABA ILAB PBFA
Seller rating 5 out of 5 stars
First Edition
Hardcover. Condition: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.
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Machine Learning : A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: As New. Unread book in perfect condition.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: New.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press CUP, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: Used. pp. 350 New edition niversity Press.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: Used. pp. 350.
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Machine Learning : A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press 2022-03-31, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Hardcover. Condition: New.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: Used. pp. 350.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Machine Learning: A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press 2022-03-31, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Hardcover. Condition: New.
-
Machine Learning : A First Course for Engineers and Scientists
Language: English
Published by Cambridge University Press, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Machine Learning
Language: English
Published by Cambridge University Press, GB, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
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Machine Learning
Language: English
Published by Cambridge University Pr., 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Condition: New. This coherent introduction to machine learning for readers with a background in basic linear algebra, statistics, probability, and programming is suitable for advanced BSc or MSc courses. It covers theory and practice of basic and advanced methods such as d.
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Hardcover. Condition: Brand New. 325 pages. 10.20x7.20x0.80 inches. In Stock.
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Machine Learning
Language: English
Published by Cambridge University Press, GB, 2022
ISBN 10: 1108843603 ISBN 13: 9781108843607
Hardback. Condition: New. This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
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Hardcover. Condition: Brand New. 325 pages. 10.20x7.20x0.80 inches. In Stock. This item is printed on demand.
