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Data Classification and Incremental Clustering in Data Mining and Machine Learning (EAI/Springer Innovations in Communication and Computing) [9783030930875]

Hardcover
SKU: 9783030930875
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Format Sturdy and long-lasting. Ideal for libraries and classrooms, and a polished choice for corporate gifts, leadership programs, or event takeaways.

Price $119.99

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Overview

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.

The book, Data Classification and Incremental Clustering in Data Mining and Machine Learning (EAI/Springer Innovations in Communication and Computing) [Bulk, Wholesale, Quantity] ISBN#9783030930875 in Hardcover by Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.

Details

Author:
Sanjay Chakraborty SK Hafizul Islam Debabrata Samanta
Format:
Hardcover
Publication Date:
05/11/2022
ISBN-13:
9783030930875
Pages:
196
Publisher:
Springer International Publishing

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