logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Data Mining and Data Warehousing: Principles and Practical Techniques by Parteek Bhatia ISBN 9781108727747, 1108727743

  • SKU: EBN-9998966
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

0.0

0 reviews
Instant download (eBook) Data Mining and Data Warehousing: Principles and Practical Techniques after payment.
Authors:Parteek Bhatia
Pages:515 pages.
Year:2019
Editon:1
Publisher:Cambridge University Press
Language:english
File Size:39.21 MB
Format:pdf
ISBNS:9781108727747, 1108727743
Categories: Ebooks

Product desciption

(Ebook) Data Mining and Data Warehousing: Principles and Practical Techniques by Parteek Bhatia ISBN 9781108727747, 1108727743

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products