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CRC Press Manifold Learning Theory and Applications - CRC Press

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Description

Manifold Learning Theory and Applications by CRC Press addresses the critical challenge of extracting meaningful structures from high-dimensional data in machine learning and computer vision applications. Engineers and scientists working with large volumes of complex data often struggle to isolate the low-dimensional patterns that drive real-world insights. This comprehensive guide explores state-of-the-art manifold learning techniques that enable dimensionality reduction across neural networks, pattern recognition, image processing, and computer vision projects. The book fills a significant gap in technical literature by combining theoretical foundations with practical applications, making it an essential resource for professionals seeking to master techniques for uncovering hidden structures within their high-dimensional datasets and improving model performance across multiple domains.

Key Features

Manifold Learning Theory and Applications covers dimensionality reduction techniques specifically designed for extracting low-dimensional structures from high-dimensional data.

This CRC Press book includes state-of-the-art methods applicable to machine learning, neural networks, pattern recognition, image processing, and computer vision.

The guide provides both theoretical foundations and practical applications for engineers and scientists working with complex, multidimensional datasets.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
06 January 2012
Listed Since
08 July 2011

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No barcode data available

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