Representation in Machine Learning by Murty, M. N.

Representation in Machine Learning (Paperback) (ISBN-13: 9789811979071)

Vendor: M. N. Murty
Product type: Books
Format: Paperback
$54.99
$54.99
$54.99
Subtotal: $54.99
Representation in Machine Learning by Murty, M. N.

Representation in Machine Learning

$54.99
Representation in Machine Learning by Murty, M. N.

Representation in Machine Learning

$54.99
Format: Paperback
Description
Description
x

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.


Author: M. N. Murty, M. Avinash
ISBN-10: 9811979073
ISBN-13: 9789811979071
Publisher: Springer
Language: English
Published: 01/21/2023
Pages: 93
Format: Paperback
Weight: 0.35lbs
Size: 9.21h x 6.14w x 0.22d
By M. N. Murty
By M. N. Murty
x

M Narasimha Murty is a prominent researcher in the areas of ML and AI. He has co-authored an introductory book on Pattern Recognition, published by Springer, that is widely used by teachers and researchers. He led the team that won the ACMKDD Cup in 2003. He has collaborated with and worked at several institutions in India, the USA and Europe.

Avinash M is a graduate student at the Indian Institute of Technology, Madras, India, whose main research interests include Signal Processing and ML. He was in the top 90 among the approximately 200,000 candidates taking the GATE (Graduate Aptitude Test in Engineering) examination in 2016 in India.

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