Foreman J. Data Smart: Using Data Science to Transform Information into Insight

Wiley, 2013. — 432 p.Data science gets thrown around in the press like it’s magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. Seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.And in Data Smart, MailChimp's Chief Scientist, John Foreman, will show you how that’s done within the hype-free, comfortable environment of a spreadsheet.Each chapter covers a different technique in a spreadsheet so you can follow along.Topics include:Mathematical optimization, including non-linear programming and genetic algorithms
Clustering via k-means, spherical k-means, and graph modularity
Data mining in graphs, such as outlier detection
Supervised AI through logistic regression, ensemble models, and bag-of-words models
Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation
Moving from spreadsheets into the R programming languageIntroduction xiii
Everything You Ever Needed to Know about Spreadsheets but Were Too Afraid to Ask
Cluster Analysis Part I: Using K-Means to Segment Your Customer Base
Naïve Bayes and the Incredible Lightness of Being an Idiot
Optimization Modeling: Because That "Fresh Squeezed" Orange Juice Ain't Gonna Blend Itself
Cluster Analysis Part II: Network Graphs and Community Detection
The Granddaddy of Supervised Artificial Intelligence—Regression
Ensemble Models: A Whole Lot of Bad Pizza
Forecasting: Breathe Easy; You Can't Win
Outlier Detection: Just Because They're Odd Doesn’t Mean They're Unimportant
Moving from Spreadsheets into R