Data science for business : [what you need to know about data mining and data-analytic thinking] - Provost, Foster, 1964-; Fawcett, Tom. (Sebastopol, Calif. : O'Reilly, 2013)
Introduction : data-analytic thinking -- Business problems and data science solutions -- Introduction to predictive modeling : from correlation to supervised segmentation -- Fitting a model to data -- Overfitting and its avoidance -- Similarity, neighbors, and clusters -- Decision analytic thinking I : what is a good model? -- Visualizing model performance -- Evidence and probabilities -- Representing and mining text -- Decision analytic thinking II : toward analytical engineering -- Other data science tasks and techniques -- Data science and business strategy -- Conclusion.
Subtitle from cover.
Includes bibliographical references (p. 359-366) and index.
Keywords: Data mining; Big data; Information science; Business -- Data processing