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Více informací o knize Feature Learning and Understanding

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Anotace knihy

This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.

Parametry knihy

Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Physik, Astronomie Physik, Astronomie - Sonstiges

• Plný název: Feature Learning and Understanding
• Autor: Xianyi Zhang, Henry Leung, Zhihui Lai
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 291
• EAN: 9783030407964
• ISBN: 3030407969
• ID: 35540776
• Nakladatelství: Springer Nature Switzerland AG
• Hmotnost: 474 g
• Rozměry: 235 × 155 × 17 mm
• Datum vydání: 04. April 2021

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