Machine learning models and algorithms for big data classification. Thinking with examples for effective learning
type: Item
instance of: scholarly article
title: Machine learning models and algorithms for big data classification. Thinking with examples for effective learning
zbMATH Open document ID: 1409.68004
DOI: 10.1007/978-1-4899-7641-3
author: S. Suthaharan
published in: Integrated Series in Information Systems
publication date: 2017-11-27T00:00:00Z
review text: This book focuses on how to address big data classification problems using different machine learning techniques. As such it provides a readable, technical, description of the whole area of machine learning applied on big data that can be understood and enjoyed by students and researchers from many areas of computer science, statistics, biology and chemistry who are seeking to understand how these new technologies can benefit their special areas. Throughout, there are lots of examples, web-links and illustrations that make it easy for the novice to appreciate the concepts. Chapter 1 provides a general introduction to Science of Information. The book then divides into four parts. The first part deals with basic concepts of big data; the second part presents big data systems, whereas parts three and four describe different machine learning techniques. Overall, this is an excellent introduction to the main ideas for using machine learning algorithms for big data classification. As such, it provides a technical description of the topic that illustrates applicability of the subject.
reviewed by: Smaranda Belciug
Mathematics Subject Classification ID: 68-01
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6813234
zbMATH Keywords: machine learning
zbMATH Keywords: big data
describes a project that uses: Matlab
describes a project that uses: R
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-1-4899-7641-3
OpenAlex ID: W2499581503
description: scientific article; zbMATH DE number 6813234