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  3. Machine learning

Inference and Learning from Data: Volume 3

- Learning
Af: Ali H. Sayed Engelsk Hardback

Inference and Learning from Data: Volume 3

- Learning
Af: Ali H. Sayed Engelsk Hardback
Tjek vores konkurrenters priser
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.
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kr 764
Fragt: 39 kr
6 - 8 hverdage
20 kr
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Tjek vores konkurrenters priser
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 990
ISBN-13: 9781009218283
Indbinding: Hardback
Udgave:
ISBN-10: 100921828X
Kategori: Machine learning
Udg. Dato: 22 dec 2022
Længde: 43mm
Bredde: 252mm
Højde: 147mm
Forlag: Cambridge University Press
Oplagsdato: 22 dec 2022
Forfatter(e): Ali H. Sayed
Forfatter(e) Ali H. Sayed

Kategori Machine learning

ISBN-13 9781009218283

Sprog Engelsk

Indbinding Hardback

Sider 990

Udgave

Længde 43mm

Bredde 252mm

Højde 147mm

Udg. Dato 22 dec 2022

Oplagsdato 22 dec 2022

Forlag Cambridge University Press

Kategori sammenhænge