An Introduction to Pattern Recognition and Machine Learning (Hardcover)
Language: English
Published by Springer Nature Switzerland AG, Cham, 2022
- First Edition
- Hardcover
- New
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Add to basketItem description from seller
Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9783030959937
- Title
- An Introduction to Pattern Recognition and Machine Learning (Hardcover)
- Author
- Paul Fieguth
- Publisher
- Springer Nature Switzerland AG, Cham
- Publication year
- 2022
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030959937
- ISBN 13
- 9783030959937
- Edition
- 1st Edition
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.
"Synopsis" may belong to another edition of this title.
About the Author
Paul Fieguth received the B.A.Sc. degree from the University of Waterloo, Canada, in 1991 and the Ph.D. degree from the Massachusetts Institute of Technology (MIT), United States, in 1995, both degrees in electrical engineering. He joined the faculty at the University of Waterloo in 1996, where he is currently Professor in Systems Design Engineering. He is a co-director of the Vision and Image Processing research group, where his research interests broadly involve machine learning for computer vision and statistical image processing. Specific interests include hierarchical algorithms for large problems, particularly in simplifying modelling and interpretation. In addition to this text, he is also the author on textbooks on Statistical Image Processing and Complex Systems.
"About the title" may belong to another edition of this title.
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