Data Mining for the Masses is written by Dr. Matthew North in 2012 licensed under common creative attribution 3.0 licensed. This book contains 3 sections and 14 chapters starting from introduction to data mining and CRISP-DM than organizational understanding and data understanding, data preparation, correlation, association rules, k-means clustering, discriminant analysis, linear regression, logistic regression, decisions trees, neural networks, text mining, evaluation and deployment, and data mining ethics. The three sections are data mining basics, data mining methods and models, and special consideration in data mining.
About author of Data Mining for the Masses:
Dr. Matt North came to the Information Systems and Technology department at UVU in 2015. His teaching expertise is in Business Information Systems, Data Mining and Analytics, Geographic Information Systems (GIS) and Web/Mobile Software Development. Research areas include Data Mining, GIS, Business & Technology Pedagogy, and Digital Ethics. He is the author of two books, Life Lessons & Leadership (Agami Press, 2011), and Data Mining for the Masses (2nd Edition, Infinite Publishing, 2016), as well as numerous journal papers, articles, book chapters, and conference presentations. An award winning professor and scholar, he is a Fulbright alumnus (Universidad Tecnológica Nacional de Argentina, 2013) and the recipient of the Ben Bauman Award for Excellence and the Gamma Sigma Alpha Outstanding Professor Award.
Dr. North loves the university’s mission with emphasis placed on student-focused undergraduate education. Several of his publications are with undergraduate student co-authors, and he is always interested in collaborating with bright and motivated young scholars. His office is in the Computer Science building 601A, and contains an impressive collection of eBay and The Simpsons memorabilia. Come by, take a look, and introduce yourself!
The second edition of Data Mining for the Masses is now available! The new edition includes two additional modeling techniques (k-Nearest Neighbors and Naive Bayes), along with implementations of all chapter examples in the R statistical language.
Have you ever found yourself working with a spreadsheet full of data and wishing you could make more sense of the numbers? Have you reviewed sales or operations reports, wondering if there’s a better way to anticipate your customers’ needs? Perhaps you’ve even thought to yourself: There’s got to be more to these figures than what I’m seeing!
Data Mining can help, and you don’t need a Ph.D. in Computer Science to do it. You can forecast staffing levels, predict demand for inventory, even sift through millions of lines of customer emails looking for common themes—all using data mining. It’s easier than you might think.
In Data Mining for the Masses, professor Matt North—a former risk analyst and database developer for eBay.com—uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions.