Applied Machine Learning for Smart Data Analysis

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Nilanjan Dey Sanjeev Wagh (Department of Information Technology, Government College of Engineering, Karad, India)

Applied Machine Learning for Smart Data Analysis

Nilanjan Dey, Sanjeev Wagh (Department of Information Technology, Government College of Engineering, Karad, India), Parikshit N. Mahalle (VIIT, Pune) , Mohd. Shafi Pathan

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English

CRC Press
05 June 2019

Data mining; Machine learning

Series: Computational Intelligence in Engineering Problem Solving

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results.

Key Features

Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications

Edited by: Nilanjan Dey, Sanjeev Wagh (Department of Information Technology, Government College of Engineering, Karad, India), Parikshit N. Mahalle (VIIT, Pune), Mohd. Shafi Pathan
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 512g
ISBN: 9781138339798
ISBN 10: 1138339792
Series: Computational Intelligence in Engineering Problem Solving
Pages: 244
Publication Date: 05 June 2019
Audience: Professional and scholarly , General/trade , Undergraduate , ELT Advanced
Format: Hardback
Publisher's Status: Active

Nilanjan Dey, Sanjeev Wagh, Parikshit N. Mahalle, Mohd. Shafi Pathan