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Data Mining - 3rd Edition by Mehmed Kantardzic (Hardcover)

Data Mining - 3rd Edition by  Mehmed Kantardzic (Hardcover) - 1 of 1
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About this item

Highlights

  • Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization.
  • About the Author: MEHMED KANTARDZIC, PHD, is a Professor in the Department of Computer Engineering and Computer Science (CECS) at the University of Louisville, and is Director of the Data Mining Lab and CECS Graduate Programs.
  • 672 Pages
  • Computers + Internet, Databases

Description



Book Synopsis



Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces

The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author--a noted expert on the topic--explains the basic concepts, models, and methodologies that have been developed in recent years.

This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that:

- Explores big data and cloud computing

- Examines deep learning

- Includes information on convolutional neural networks (CNN)

- Offers reinforcement learning

- Contains semi-supervised learning and S3VM

- Reviews model evaluation for unbalanced data

Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.



From the Back Cover



PRESENTS THE LATEST TECHNIQUES FOR ANALYZING AND EXTRACTING INFORMATION FROM LARGE AMOUNTS OF DATA IN HIGH-DIMENSIONAL DATA SPACES

The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author--a noted expert on the topic--explains the basic concepts, models, and methodologies that have been developed in recent years.

This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that:

  • Explores big data and cloud computing
  • Examines deep learning
  • Includes information on convolutional neural networks (CNN)
  • Offers reinforcement learning
  • Contains semi-supervised learning and S3VM
  • Reviews model evaluation for unbalanced data

Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.



About the Author



MEHMED KANTARDZIC, PHD, is a Professor in the Department of Computer Engineering and Computer Science (CECS) at the University of Louisville, and is Director of the Data Mining Lab and CECS Graduate Programs. He is a member of IEEE, ISCA, KAS, WSEAS, IEE, and SPIE.

Dimensions (Overall): 9.1 Inches (H) x 6.1 Inches (W) x 1.2 Inches (D)
Weight: 1.95 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 672
Genre: Computers + Internet
Sub-Genre: Databases
Publisher: Wiley-IEEE Press
Theme: Data Mining
Format: Hardcover
Author: Mehmed Kantardzic
Language: English
Street Date: November 12, 2019
TCIN: 1005681739
UPC: 9781119516040
Item Number (DPCI): 247-36-8155
Origin: Made in the USA or Imported

Shipping details

Estimated ship dimensions: 1.2 inches length x 6.1 inches width x 9.1 inches height
Estimated ship weight: 1.95 pounds
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