Machine Learning for Big Data Analysis

Machine Learning for Big Data Analysis
Author :
Publisher : Walter de Gruyter GmbH & Co KG
Total Pages : 194
Release :
ISBN-10 : 9783110551433
ISBN-13 : 3110551438
Rating : 4/5 (438 Downloads)

Book Synopsis Machine Learning for Big Data Analysis by : Siddhartha Bhattacharyya

Download or read book Machine Learning for Big Data Analysis written by Siddhartha Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-12-17 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent research.


Machine Learning for Big Data Analysis Related Books

Machine Learning for Big Data Analysis
Language: en
Pages: 194
Authors: Siddhartha Bhattacharyya
Categories: Computers
Type: BOOK - Published: 2018-12-17 - Publisher: Walter de Gruyter GmbH & Co KG

GET EBOOK

This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics
Advanced Deep Learning Applications in Big Data Analytics
Language: en
Pages: 351
Authors: Bouarara, Hadj Ahmed
Categories: Computers
Type: BOOK - Published: 2020-10-16 - Publisher: IGI Global

GET EBOOK

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order
Machine Learning Paradigms
Language: en
Pages: 230
Authors: Maria Virvou
Categories: Technology & Engineering
Type: BOOK - Published: 2019-03-16 - Publisher: Springer

GET EBOOK

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced
Applications of Machine Learning in Big-Data Analytics and Cloud Computing
Language: en
Pages: 346
Authors: Subhendu Kumar Pani
Categories: Technology & Engineering
Type: BOOK - Published: 2022-09-01 - Publisher: CRC Press

GET EBOOK

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine tim
Advances in Machine Learning for Big Data Analysis
Language: en
Pages: 254
Authors: Satchidananda Dehuri
Categories: Technology & Engineering
Type: BOOK - Published: 2022-02-24 - Publisher: Springer Nature

GET EBOOK

This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book,