Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

4,33 valoración promedio
( 12 valoraciones por Goodreads )
 
9780470074718: Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

A practical, step-by-step approach to making sense out of data

Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data.

Readers are given a solid foundation in the procedures associated with complex data analysis or data mining projects and are provided with concrete discussions of the most universal tasks and technical solutions related to the analysis of data, including:
* Problem definitions
* Data preparation
* Data visualization
* Data mining
* Statistics
* Grouping methods
* Predictive modeling
* Deployment issues and applications

Throughout the book, the author examines why these multiple approaches are needed and how these methods will solve different problems. Processes, along with methods, are carefully and meticulously outlined for use in any data analysis or data mining project.

From summarizing and interpreting data, to identifying non-trivial facts, patterns, and relationships in the data, to making predictions from the data, Making Sense of Data addresses the many issues that need to be considered as well as the steps that need to be taken to master data analysis and mining.

"Sinopsis" puede pertenecer a otra edición de este libro.

About the Author:

GLENN J. MYATT, PhD, is cofounder of Leadscope, Inc., a data mining company providing solutions to the pharmaceutical and chemical industry. He has also acted as a part-time lecturer in chemoinformatics at The Ohio State University and has held a series of industrial and academic research positions. Dr. Myatt is the author of numerous journal articles.

Review:

“This book is written in plain language and is useful to you who wants to learn about the business of gathering and analyzing data and accomplishing the objectives you set beforehand. Its most important message I think is that you define the problem so that the data gathered will be tailored to solving it.”  (Biz India, 22 December 2012)

"...a well-written book on data analysis and data mining that provides an excellent foundation..." (CHOICE, May 2007)

"This is a must-read book for learning practical statistics and data analysis" (Computing Reviews.com, May 22, 2007)

"...the book should be accessible to all its intended readers." (MAA Reviews, December 28, 2006)

"Sobre este título" puede pertenecer a otra edición de este libro.

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Myatt, Glenn J.
ISBN 10: 047007471X ISBN 13: 9780470074718
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Glenn J. Myatt
Editorial: Wiley-Interscience (2006)
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Editorial: Hoboken, New Jersey, U.S.A.: Wiley-Interscience (2006)
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