Support Vector Machines Applications - Image 1

£99.99

Springer Support Vector Machines Applications

Name: Support Vector Machines Applications
Brand: Springer
Price: 99.99 GBP
Availability: InStock

AI & Machine Learning

Price History & Forecast

Last 43 days • 43 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 43 days • 1 price levels

Days at Price

Price Analysis

Most common price: £100 (43 days, 100.0%)

Price range: £100 - £100

Price levels: 1 different prices over 43 days

Description

Product Description Offering a detailed, unified approach, this book examines advances and applications of Support Vector Machines: image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, artificial intelligence and more. Review From the book reviews:“The book brings substantial contributions to the field of SVMs from both theoretical and practical points of view. The concepts and methods are presented in a clear and accessible way, and the illustrative examples and applications provide a valuable source of inspiration for similar developments. … This book is of considerable value to researchers in the fields of machine learning, data mining, and statistical pattern recognition.” (L. State, Computing Reviews, August, 2014) From the Back Cover Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances. About the Author Yunqian Ma is Senior Principal Research Scientist at Honeywell Labs. Guodong Guo is an Assistant Professor at West Virginia University.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 3319343297
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 03 September 2016
Listed Since: 25 August 2016

Barcode

No barcode data available

Springer Support Vector Machines Applications

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Springer Support Vector Machines Applications Book

Springer Support Vector Machines for Pattern Classification

Rule Extraction from Support Vector Machines: 80 (Studies in Computational Intelligence, 80)

CRC Press - Support Vector Machines in Chemistry and Biotech

Machine Learning: A Practical Approach on the Statistical Learning Theory

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

Optimization Based Data Mining: Theory and Applications (Advanced Information and Knowledge Processing)

Machine Learning and its Applications

Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications: 18 (Learning and Analytics in Intelligent Systems, 18)

Applied Machine Learning

Support Vector Machines and Evolutionary Algorithms for Classification: Single or Together?: 69 (Intelligent Systems Reference Library, 69)

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)

John Wiley & Sons Data Mining and Machine Learning Applications

Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (Statistics and Computing)

Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (Statistics and Computing)

Machine Learning Methods

Advanced Topics in Computer Vision (Advances in Computer Vision and Pattern Recognition)

Machine Learning and Big Data: Concepts, Algorithms, Tools and Applications

Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing (Advances in Computer Vision and Pattern Recognition)

Advances in Big Data Analytics: Theory, Algorithms and Practices

Automated Machine Learning and Meta-Learning for Multimedia: Approaches and Applications

Learning Representation for Multi-View Data Analysis: Models and Applications (Advanced Information and Knowledge Processing)

Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/CRC Machine Learning & Pattern Recognition)