M. N. Murty & M. Avinash 
Representation in Machine Learning [PDF ebook] 

Destek


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.

€53.49
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İçerik tablosu

1. Introduction.- 2. Representation.- 3. Nearest Neighbor Algorithms.- 4. Representation Using Linear Combinations.- 5. Non-Linear Schemes for Representation.- 6. Conclusions.

Yazar hakkında

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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Dil İngilizce ● Biçim PDF ● Sayfalar 93 ● ISBN 9789811979088 ● Dosya boyutu 4.3 MB ● Yayımcı Springer Nature Singapore ● Kent Singapore ● Ülke SG ● Yayınlanan 2023 ● İndirilebilir 24 aylar ● Döviz EUR ● Kimlik 8796351 ● Kopya koruma Sosyal DRM

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