£99.99

Springer - Multiview Machine Learning Textbook

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Description

Explore one of the fastest growing branches of machine learning with Multiview Machine Learning by Springer. This book offers a deep discussion of multiview learning, a field that has demonstrated strong theoretical foundations and significant practical success in real data analysis. Learn how to incorporate multiple views to improve generalization performance. This process, often referred to as data fusion or data integration from multiple feature sets, is essential for modern data science. The text provides a comprehensive look at the various models and algorithms used to handle complex datasets. Designed as a self-contained resource, this book is highly applicable to multi-modal learning research. It is written to be accessible, requiring minimal prior knowledge to get started. Whether you are studying data integration or advanced machine learning models, this book serves as a practical guide to mastering multiview techniques.

Key Features

Provides an in-depth discussion of multiview learning, covering one of the most rapidly developing areas in the machine learning field.

Explains essential models and algorithms used for effective real data analysis and practical application.

Covers data fusion and data integration methods to help improve generalization performance through multiple feature sets.

Serves as a self-contained resource that is highly applicable to researchers working in multi-modal learning.

Designed for accessibility, requiring minimal prior knowledge to begin studying these advanced machine learning concepts.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
17 January 2019
Listed Since
20 September 2018

Barcode

No barcode data available

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