Machine learning refined : foundations, algorithms, and applications /
The second edition of this text is a complete revision of our first endeavor, with virtually every chapter of the original rewritten from the ground up and eight new chapters of material added, doubling the size of the first edition. Topics from the first edition, from expositions on gradient descen...
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | Book |
| Language: | English |
| Published: |
Cambridge ; New York :
Cambridge University Press,
[2020].
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| Edition: | Second edition. |
| Subjects: |
| Summary: | The second edition of this text is a complete revision of our first endeavor, with virtually every chapter of the original rewritten from the ground up and eight new chapters of material added, doubling the size of the first edition. Topics from the first edition, from expositions on gradient descent to those on One-versus- All classification and Principal Component Analysis have been reworked and polished. A swath of new topics have been added throughout the text, from derivative-free optimization to weighted supervised learning, feature selection, nonlinear feature engineering, boosting-based cross-validation and more. |
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| Physical Description: | xxi, 574 pages : illustrations (some color) ; 26 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781108480727 1108480721 |