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Applied Machine Learning for Smart Data Analysis

AUTHOR Mahalle, Parikshit N.; Wagh, Sanjeev; Dey, Nilanjan et al.
PUBLISHER CRC Press (05/29/2019)
PRODUCT TYPE Hardcover (Hardcover)

Description

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
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Product Format
Product Details
ISBN-13: 9781138339798
ISBN-10: 1138339792
Binding: Hardback or Cased Book (Sewn)
Content Language: English
More Product Details
Page Count: 244
Carton Quantity: 12
Feature Codes: Bibliography, Index
Country of Origin: US
Subject Information
BISAC Categories
Computers | Data Science - Data Analytics
Computers | Machine Theory
Computers | Electronics - General
Dewey Decimal: 006.312
Library of Congress Control Number: 2018033217
Descriptions, Reviews, Etc.
publisher marketing

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
Show More
List Price $180.00
Your Price  $178.20
Hardcover