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portada Kernel Methods and Machine Learning
Type
Physical Book
Year
2014
Language
English
Pages
572
Format
Hardcover
ISBN13
9781107024960
Edition No.
1

Kernel Methods and Machine Learning

S. Y. Kung (Author) · Cambridge University Press · Hardcover

Kernel Methods and Machine Learning - S. Y. Kung

New Book Imported to South Africa
Delivery: 07 Aug - 17 Aug Shipping: 5 to 6 business days.
R 2,449
R 2,449

Synopsis "Kernel Methods and Machine Learning "

Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

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