Advances in Machine Learning for Big Data Analysis (Hardcover, 1st ed. 2022)

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, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Intelligent Systems Reference Library, 218
Release date:	March 2022
First published:	2022
Editors:	Satchidananda Dehuri • Yen-Wei Chen
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	239
Edition:	1st ed. 2022
ISBN-13:	978-981-16-8929-1
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Databases > Data capture & analysis Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	981-16-8929-6
Barcode:	9789811689291

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