Representation in Machine Learning

Name: Representation in Machine Learning
Brand: Springer, Berlin
SKU: 9789811979071
Price: 1260 CZK
Availability: InStock

Autor: M. N. Murty, M. Avinash

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer, Berlin

Dostupnost: Skladem u dodavatele

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This book provides a concise but comprehensive guide to representation, which forms the core of Mach...

Informace o knize

Autor

M. N. Murty, M. Avinash

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2023

Stránek

EAN

9789811979071

Enbook ID

41636719

Vydavatel

Springer, Berlin

Hmotnost

159

Rozměry

155 x 235

Kompletní popis

This book provides a concise but comprehensive guide to representation, which forms the core of Machine Learning (ML). State-of-the-art practical applications involve a number of challenges for the analysis of high-dimensional data. Unfortunately, many popular ML algorithms fail to perform, in both theory and practice, when they are confronted with the huge size of the underlying data. Solutions to this problem are aptly covered in the book.In addition, the book covers a wide range of representation techniques that are important for academics and ML practitioners alike, such as Locality Sensitive Hashing (LSH), Distance Metrics and Fractional Norms, Principal Components (PCs), Random Projections and Autoencoders. Several experimental results are provided in the book to demonstrate the discussed techniques' effectiveness.

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