Machine learning refined :
Material type:
TextEdition: Second EditionDescription: pages cmISBN: 9781108480727Subject(s): Machine learningDDC classification: 006.3/1 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"--
| Item type | Current library | Call number | Status | Date due | Barcode |
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Books
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Jos Study Centre Book Cart | QA325.5 .W38 2020 (Browse shelf(Opens below)) | Available | 0183158 | |
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Books
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Gabriel Afolabi Ojo Central Library (Headquarters). | Q325.5 .M33 2020 (Browse shelf(Opens below)) | Available | 0162893 |
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| Q188.4 .E64 2017 Enhancing learning with effective practical science 11-16 / | Q23.2 .U36 2019 E`YA` ARA FUN ALAKOOBERE Anatomy for Beginners ( Human and Veterinary)) | Q276 .A53 1986 Statistics : | Q325.5 .M33 2020 Machine learning refined : | Q33 .A58 2020 Integrated science in digital age 2020 / | Q33.3 .T36 2016 GPU-based parallel implementation of swarm intelligence algorithms / | Q337.3 .T36 2016 GPU-based parallel implementation of swarm intelligence algorithms / |
First edition published 2016.
"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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