



Machine Learning in Data ProcessingAuthor(s): Xiang-Sheng Wang, Chisheng Wang
Format: Hardback
Publisher: Springer Nature Switzerland AG, Switzerland
Imprint: Springer Nature Switzerland AG
ISBN-13: 9783032208545, 978-3032208545
Synopsis
Machine learning has become a cornerstone of modern data-driven science and technology. For mathematics students and researchers, understanding the mathematical foundations behind machine learning is essential, even if they never work directly with real-world datasets.
This book provides a rigorous yet accessible introduction to the core mathematical ideas that underpin machine learning. Topics such as linear and nonlinear regression, regularization techniques, and the fundamentals of neural networks are explained in detail from a clear mathematical perspective.
Unlike many existing texts that emphasize coding and practical implementation, this book focuses on theoretical results and conceptual understanding. It is designed for readers wh.
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Machine Learning in Data ProcessingAuthor(s): Xiang-Sheng Wang, Chisheng Wang
Format: Hardback
Publisher: Springer Nature Switzerland AG, Switzerland
Imprint: Springer Nature Switzerland AG
ISBN-13: 9783032208545, 978-3032208545
Synopsis
Machine learning has become a cornerstone of modern data-driven science and technology. For mathematics students and researchers, understanding the mathematical foundations behind machine learning is essential, even if they never work directly with real-world datasets.
This book provides a rigorous yet accessible introduction to the core mathematical ideas that underpin machine learning. Topics such as linear and nonlinear regression, regularization techniques, and the fundamentals of neural networks are explained in detail from a clear mathematical perspective.
Unlike many existing texts that emphasize coding and practical implementation, this book focuses on theoretical results and conceptual understanding. It is designed for readers wh.
Price now:
From
To
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Machine Learning in Data ProcessingAuthor(s): Xiang-Sheng Wang, Chisheng Wang
Format: Hardback
Publisher: Springer Nature Switzerland AG, Switzerland
Imprint: Springer Nature Switzerland AG
ISBN-13: 9783032208545, 978-3032208545
Synopsis
Machine learning has become a cornerstone of modern data-driven science and technology. For mathematics students and researchers, understanding the mathematical foundations behind machine learning is essential, even if they never work directly with real-world datasets.
This book provides a rigorous yet accessible introduction to the core mathematical ideas that underpin machine learning. Topics such as linear and nonlinear regression, regularization techniques, and the fundamentals of neural networks are explained in detail from a clear mathematical perspective.
Unlike many existing texts that emphasize coding and practical implementation, this book focuses on theoretical results and conceptual understanding. It is designed for readers wh.
General | |
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format | hardback |
Language | english |
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