Data science for business: What you need to know about data mining and data-analytic thinking
By: Provost, Foster.
Contributor(s): Tom Fawcett.Publisher: California, U.S. : Sebastopol O'Reilly , 2013Description: 620 p. Digital.Subject(s): CIENCIA Y TECNOLOGÍA | CIENCIA DE DATOS | CIENTÍFICO DE DATOS | MINERÍA DE DATOSDDC classification: Recurso digital Online resources: ►►DOWNLOAD EBOOK / DESCARGAR LIBRO DIGITAL◄◄
|Item type||Current location||Collection||Call number||Status||Date due||Barcode|
|Libro Digital||Biblioteca Lead University||Colección de reserva||Digital (Browse shelf)||Available||001|
REFERENCIA APA: Provost, F. y Fawcett, T. (2013). Data Science for Business: What you need to know about Data Mining and Data-Analytic thinking. California, U.S.: O'Reilly Media.
Contents: 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 II: toward analytical engineering. Other data science tasks and techniques. Data science and business strategy. Conclusion.