Amazon cover image
Image from Amazon.com
Image from Google Jackets
Image from OpenLibrary

Fundamentals of Data Analytics: with a View to Machine Learning/ Rudolf Mathar, Gholamreza Alirezaei, Emilio Balda, Arash Behboodi

By: Contributor(s): Material type: TextTextPublication details: Switzerland : Springer Nature, 2020.Description: xi, 127 p. illISBN:
  • 9783030568337
Subject(s): DDC classification:
  • 006.31 MAT
Other classification:
Contents:
1 Introduction.- 2 Prerequisites from Matrix Analysis.- 3 Multivariate Distributions and Moments.- 4 Dimensionality Reduction.- 5 Classification and Clustering.- 6 Support Vector Machines.- 7 Machine Learning.- Index.
Summary: This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Home library Collection Call number Status Date due Barcode
Book Book Dept. of Futures Studies General Stacks Dept. of Futures Studies Non-fiction 006.31 MAT (Browse shelf(Opens below)) Available DFS4604

1 Introduction.- 2 Prerequisites from Matrix Analysis.- 3 Multivariate Distributions and Moments.- 4 Dimensionality Reduction.- 5 Classification and Clustering.- 6 Support Vector Machines.- 7 Machine Learning.- Index.

This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.

There are no comments on this title.

to post a comment.