An Introduction to Pattern Recognition and Machine Learning (Hardcover, 1st ed. 2022)

The domains of Pattern Recognition and Machine Learning have experienced exceptional interest and growth, however the overwhelming number of methods and applications can make the fields seem bewildering. This text offers an accessible and conceptually rich introduction, a solid mathematical development emphasizing simplicity and intuition. Students beginning to explore pattern recognition do not need a suite of mathematically advanced methods or complicated computational libraries to understand and appreciate pattern recognition; rather the fundamental concepts and insights, eminently teachable at the undergraduate level, motivate this text. This book provides methods of analysis that the reader can realistically undertake on their own, supported by real-world examples, case-studies, and worked numerical / computational studies.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	November 2022
First published:	2022
Authors:	Paul Fieguth
Dimensions:	235 x 155 x 37mm (L x W x T)
Format:	Hardcover
Pages:	471
Edition:	1st ed. 2022
ISBN-13:	978-3-03-095993-7
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Social sciences > Sociology, social studies > Social research & statistics > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	3-03-095993-7
Barcode:	9783030959937

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