Name: Data Classification and Incremental Clustering in Data Mining and Machine Learning
Price: 1495.00 ZAR
Availability: InStock
Author: Chakraborty, Sanjay ; Islam, Sk Hafizul ; Samanta, Debabrata
ISBN: 9783030930905

portada Data Classification and Incremental Clustering in Data Mining and Machine Learning

Data Classification and Incremental Clustering in Data Mining and Machine Learning

Type

Physical Book

Author

Publisher

Language

English

Pages

196

Format

Paperback

Dimensions

23.4 x 15.6 x 1.2 cm

Weight

0.31 kg.

ISBN13

9783030930905

Synopsis "Data Classification and Incremental Clustering in Data Mining and Machine Learning"

This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc, ) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

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Data Classification and Incremental Clustering in Data Mining and Machine Learning - Chakraborty, Sanjay ; Islam, Sk Hafizul ; Samanta, Debabrata

Synopsis "Data Classification and Incremental Clustering in Data Mining and Machine Learning"

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