Introduction to Data Mining

Introduction to Data Mining Using SAS Enterprise Miner  eBooks & eLearning

Posted by phidhahoogaya at Aug. 1, 2011
Introduction to Data Mining Using SAS Enterprise Miner

Introduction to Data Mining Using SAS Enterprise Miner
SAS Publishing | February 16, 2007 | ISBN-10: 1590478290 | 468 pages | PDF | 14.8 MB

If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, Introduction to Data Mining Using SAS Enterprise Miner provides

Discovering Knowledge in Data: An Introduction to Data Mining  eBooks & eLearning

Posted by Bayron at July 29, 2014
Discovering Knowledge in Data: An Introduction to Data Mining

Discovering Knowledge in Data: An Introduction to Data Mining by Daniel T. Larose, Chantel D. Larose
English | 2014 | ISBN: 0470908742 | 336 pages | PDF, EPUB | 6 MB, 10 MB

Introduction to Data Mining for the Life Sciences (repost)  eBooks & eLearning

Posted by Veslefrikk at Feb. 8, 2014
Introduction to Data Mining for the Life Sciences (repost)

Rob Sullivan, "Introduction to Data Mining for the Life Sciences"
Publisher: H.m.na Pr.ss | ISBN: 1588299422 | 2011 | PDF | 648 pages | 16 MB

Discovering Knowledge in Data: An Introduction to Data Mining (repost)  eBooks & eLearning

Posted by Veslefrikk at Nov. 19, 2013
Discovering Knowledge in Data: An Introduction to Data Mining (repost)

Discovering Knowledge in Data: An Introduction to Data Mining
Wiley-Interscience | 2004-11-18 | ISBN: 0471666572 | 240 pages | PDF | 3,9 MB

Discovering Knowledge in Data: An Introduction to Data Mining (Reupload)  eBooks & eLearning

Posted by tot167 at Nov. 18, 2008
Discovering Knowledge in Data: An Introduction to Data Mining (Reupload)

Daniel T. Larose " Discovering Knowledge in Data: An Introduction to Data Mining"
Wiley-Interscience | 2004-11-18 | ISBN: 0471666572 | 240 pages | PDF | 3,9 MB

Introduction to Data Mining and its Applications  eBooks & eLearning

Posted by ertugrul ergun at April 15, 2007
Introduction to Data Mining and its Applications

Introduction to Data Mining and its Applications (Studies in Computational Intelligence)
Springer | ISBN / ASIN:3540343504 | Year:2006 | 828 pages | PDF | 5.3MB

This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications.

An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement  eBooks & eLearning

Posted by Sangviniy at March 23, 2017
An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement

An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement by R Ramanathan
English | Aug. 18, 2003 | ISBN: 0761997601 | 202 Pages | PDF | 2.52 MB

From the Foreword:

'This book is an excellent tool for practitioners who are interested in the merits and pitfalls of the technique…. (The author's) research is an example of inventiveness, diligence and accuracy' - Freerk A. Lootsma, Delft Institute of Technology

Beginner's Guide to Data Analytics  eBooks & eLearning

Posted by naag at March 15, 2017
Beginner's Guide to Data Analytics

Beginner's Guide to Data Analytics by O Theobald
English | 11 Mar. 2017 | ASIN: B06XJZBJD9 | 80 Pages | PDF + EPUB (conv) | 1.17 MB

Beginner's Guide to Data Analytics [Kindle Edition]  eBooks & eLearning

Posted by AlenMiler at March 13, 2017
Beginner's Guide to Data Analytics [Kindle Edition]

Beginner's Guide to Data Analytics by O Theobald
English | 11 Mar. 2017 | ASIN: B06XJZBJD9 | 80 Pages | AZW3 | 471.56 KB
Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications

Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications By Laura Igual, Santi Seguí
English | PDF,EPUB | 2017 | 257 Pages | ISBN : 3319500163 | 11.13 MB

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis.