0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R2,500 - R5,000 (2)
  • -
Status
Brand

Showing 1 - 2 of 2 matches in All Departments

Feature Learning and Understanding - Algorithms and Applications (Hardcover, 1st ed. 2020): Haitao Zhao, Zhihui Lai, Henry... Feature Learning and Understanding - Algorithms and Applications (Hardcover, 1st ed. 2020)
Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang
R3,630 Discovery Miles 36 300 Ships in 12 - 17 working days

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.

Feature Learning and Understanding - Algorithms and Applications (Paperback, 1st ed. 2020): Haitao Zhao, Zhihui Lai, Henry... Feature Learning and Understanding - Algorithms and Applications (Paperback, 1st ed. 2020)
Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang
R3,992 Discovery Miles 39 920 Ships in 10 - 15 working days

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.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Knock At The Cabin
Dave Bautista, Jonathan Groff, … DVD R133 Discovery Miles 1 330
Bostik Wax Twisters (12 Pack)
R81 R61 Discovery Miles 610
Cadac Pizza Stone (33cm)
 (18)
R398 Discovery Miles 3 980
Casio LW-200-7AV Watch with 10-Year…
R999 R884 Discovery Miles 8 840
Bostik Double-Sided Tape (18mm x 10m…
 (1)
R31 Discovery Miles 310
Vital BabyŽ NURTURE™ Ultra-Comfort…
R30 R23 Discovery Miles 230
Loot
Nadine Gordimer Paperback  (2)
R383 R310 Discovery Miles 3 100
Aerolatte Cappuccino Art Stencils (Set…
R110 R95 Discovery Miles 950
Dog's Life Calming Cuddler (Grey…
R450 R249 Discovery Miles 2 490
Vital BabyŽ HYGIENE™ Super Soft Hand…
R45 Discovery Miles 450

 

Partners