Description
| Product ID: | 9783030959937 |
| Product Form: | Hardback |
| Country of Manufacture: | GB |
| Title: | An Introduction to Pattern Recognition and Machine Learning |
| Authors: | Author: Paul Fieguth |
| Page Count: | 471 |
| Subjects: | Cybernetics and systems theory, Cybernetics & systems theory, Electronics engineering, Data mining, Expert systems / knowledge-based systems, Pattern recognition, Digital signal processing (DSP), Electronics engineering, Data mining, Expert systems / knowledge-based systems, Pattern recognition, Signal processing |
| Description: | 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. 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. |
| Imprint Name: | Springer Nature Switzerland AG |
| Publisher Name: | Springer Nature Switzerland AG |
| Country of Publication: | GB |
| Publishing Date: | 2022-11-10 |
