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Machine Learning: A Bayesian and Optimization Perspective
Language: English
Published by Academic Press (edition 2), 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Hardcover. Condition: Good. 2. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Hardcover. Condition: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
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Hardcover. 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!
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Machine Learning: A Bayesian and Optimization Perspective
Seller: Once Upon A Time Books, Siloam Springs, AR, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Good. This is a used book in good condition and may show some signs of use or wear . This is a used book in good condition and may show some signs of use or wear .
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Condition: new.
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Hardcover. Condition: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
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Condition: New.
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Condition: As New. Unread book in perfect condition.
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Machine Learning: A Bayesian and Optimization Perspective
Language: English
Published by Academic Press 2020-03-20, 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Hardcover. Condition: New.
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Machine Learning : A Bayesian and Optimization Perspective
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning: A Bayesian and Optimization Perspective
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Machine Learning : A Bayesian and Optimization Perspective
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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Hardcover. Condition: Brand New. 2nd edition. 1071 pages. 9.25x7.50x2.25 inches. In Stock.
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Machine Learning: A Bayesian and Optimization Perspective
Language: English
Published by Elsevier Science Publishing Co Inc, 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2020. 2nd Edition. Hardcover. . . . . .
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Machine Learning: A Bayesian and Optimization Perspective
Language: English
Published by Elsevier Science Publishing Co Inc, 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Condition: New. 2020. 2nd Edition. Hardcover. . . . . . Books ship from the US and Ireland.
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Machine Learning: A Bayesian and Optimization Perspective
Seller: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, United Kingdom
Seller rating 5 out of 5 stars
Condition: Fine. Light scuffs & scratches to the hardcover. Faint marks to the edges of the textblock. Content is in very good, clean condition/like new.
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Condition: New. Presents the physical reasoning, mathematical modeling and algorithmic implementation of each method Updates on the latest trends, including sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces,.
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Machine Learning : A Bayesian and Optimization Perspective
Language: English
Published by Elsevier Science Jul 2020, 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Buch. Condition: Neu. Neuware - Presents the physical reasoning, mathematical modeling and algorithmic implementation of each method Updates on the latest trends, including sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling Provides case studies on a variety of topics, including protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, and more.
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Machine Learning | A Bayesian and Optimization Perspective
Language: English
Published by Elsevier Science Publishing Co Inc, 2020
ISBN 10: 0128188030 ISBN 13: 9780128188033
Buch. Condition: Neu. Machine Learning | A Bayesian and Optimization Perspective | Sergios Theodoridis | Buch | Geheftet | Englisch | 2020 | Elsevier Science Publishing Co Inc | EAN 9780128188033 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2017-05-01 Pages: $number Publisher: Machinery Industry Press This book explores all major machine learning methods and new research trends. including probabilistic and deterministic methods and Bayesian inference methods. Among them. the classical methods include average small square filter. Kalman filter. stochastic approximation and online learning. Bayesian classification. decision .
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Machine Learning: Bayesian and Optimization Methods (Original Book 2nd Edition)(Chinese Edition)
Published by Machinery Industry Press, 2022
ISBN 10: 7111692578 ISBN 13: 9787111692577
paperback. Condition: New. Paperback.Pub Date:2022-01-01 Pages:828 Language:Chinese Publisher:Machinery Industry Press Machine Learning: Bayesian and Optimization Methods (Original Book 2nd Edition) for all important machine learning methods and recent research The trend has been deeply explored. By explaining the two pillars of supervised learningregression and classification. these complicated methods are opened up one by one from a panoramic perspective. forming a clear machine learning knowledge system. The new edi.
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paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2020-12-01 Pages:1152 Publisher: Machinery Industry Press This book introduces the two pillars of supervised learning-regression and classification-and brings machine learning into a unified perspective to discuss.?The book first discusses basic knowledge. including mean squares. *small squares and maximum likelihood methods. ridge regression. Bayesian decision theory classification. logistic regression. and decision trees.?Then introduce the latest techn.
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Machine Learning: Bayesian and Optimization Methods (Original Book 2nd Edition)(Chinese Edition)
Language: English
ISBN 10: 7111692578 ISBN 13: 9787111692577
paperback. Condition: New. Paperback.Pub Date:2022-01-01 Pages:828 Language:Chinese Publisher:Machinery Industry Press Machine Learning: Bayesian and Optimization Methods (Original Book 2nd Edition) for all important machine learning methods and recent research The trend has been deeply explored. By explaining the two pillars of supervised learningregression and classification. these complicated methods are opened up one by one from a panoramic perspective. forming a clear machine learning knowledge system. The new edi.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts.The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models.All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods.The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling.Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied.MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.
