Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition

Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition provides a comprehensive and in-depth analysis of theoretical foundations and practical applications of machine learning and pattern recognition. Authored by leading experts in the field, this authoritative reference work covers a wide range of topics, including supervised learning, unsupervised learning, dimensionality reduction, feature selection, and neural networks.

Sparse Modeling: Theory, Algorithms, and Applications (Chapman & Hall/Crc Machine Learning & Pattern Recognition)

by Irina Rish

5 out of 5

Language	:	English
File size	:	22890 KB
Screen Reader	:	Supported
Print length	:	253 pages

FREE

Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition is an essential resource for researchers, practitioners, and students in the fields of machine learning, pattern recognition, and related areas.

Key Features

• Provides a comprehensive and in-depth analysis of theoretical foundations and practical applications of machine learning and pattern recognition
• Authored by leading experts in the field
• Covers a wide range of topics, including supervised learning, unsupervised learning, dimensionality reduction, feature selection, and neural networks
• Essential resource for researchers, practitioners, and students in the fields of machine learning, pattern recognition, and related areas

Table of Contents

2. Supervised Learning
3. Unsupervised Learning
4. Dimensionality Reduction
5. Feature Selection
6. Neural Networks
7. Applications

Reviews

"Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition is a comprehensive and in-depth analysis of theoretical foundations and practical applications of machine learning and pattern recognition. Authored by leading experts in the field, this authoritative reference work covers a wide range of topics, including supervised learning, unsupervised learning, dimensionality reduction, feature selection, and neural networks. Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition is an essential resource for researchers, practitioners, and students in the fields of machine learning, pattern recognition, and related areas."

- Professor Jiawei Han, University of Illinois at Urbana-Champaign

"Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition is a must-have reference for anyone working in the field of machine learning or pattern recognition. This authoritative volume provides a comprehensive overview of the theoretical foundations and practical applications of these rapidly evolving fields. I highly recommend it to researchers, practitioners, and students alike."

- Professor Christopher Bishop, University of Cambridge

Order Your Copy Today

Theory, Algorithms and Applications: Chapman Hall/CRC Machine Learning & Pattern Recognition is available in print and electronic formats. To order your copy, please visit the Chapman & Hall/CRC website.

Sparse Modeling: Theory, Algorithms, and Applications (Chapman & Hall/Crc Machine Learning & Pattern Recognition)

by Irina Rish

5 out of 5

Language	:	English
File size	:	22890 KB
Screen Reader	:	Supported
Print length	:	253 pages

FREE