Data smart : Using data science to transform information into insight / John W. Foreman ; Edición Carol Long.

Por: Foreman, John WColaborador(es): Long, Carol [Editor]Tipo de material: TextoTextoEditor: Indianapolis : John Wiley & Sons, Inc., 2014Descripción: 409 páginas : Ilustraciones, gráficosISBN: 9781118661468Tema(s): Análisis del comportamiento de los usuarios de Internet | Procesamiento de datos | Concepción Web de SitiosClasificación CDD: 005.74
Contenidos parciales:
1. Everything you ever needed to know about spreadsheets but were too afraid to ask. -- 2. Cluster analysis part I: Using K-Means to segment your customer base. -- 3. Naive bayes and the incredible lightness of being an idiot. -- 4. Optimization modeling: Because that "Fresh Squeezed" orange juice ain't gonna blend itself. -- 5. Cluster analysis Part II: Network graphs and community detection. -- 6. The grannaddy of supervised artificial intelligence-Regression. -- 7. Ensemble models: A whole lot of bad pizza. -- 8. Forecasting: Breathe easy; you can't win. -- 9. Outlier detection: Just because they're odd doesn´t mean the're unimportant. -- 10. Moving from spreadsheets into R. --
Resumen: "Not to disillusion you, but data scientists are not mystical practitioners of magical arts. Data science is something you can do. Really. This book shows you the significant data science techniques, how they work, how to use them, and how they bebefit your business, large or small".
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CIENCIAS PURAS
005.74 F715d (Navegar estantería) Ej.1 En catalogación OK 61934

Incluye índice y conclusión.

1. Everything you ever needed to know about spreadsheets but were too afraid to ask. -- 2. Cluster analysis part I: Using K-Means to segment your customer base. -- 3. Naive bayes and the incredible lightness of being an idiot. -- 4. Optimization modeling: Because that "Fresh Squeezed" orange juice ain't gonna blend itself. -- 5. Cluster analysis Part II: Network graphs and community detection. -- 6. The grannaddy of supervised artificial intelligence-Regression. -- 7. Ensemble models: A whole lot of bad pizza. -- 8. Forecasting: Breathe easy; you can't win. -- 9. Outlier detection: Just because they're odd doesn´t mean the're unimportant. -- 10. Moving from spreadsheets into R. --

"Not to disillusion you, but data scientists are not mystical practitioners of magical arts. Data science is something you can do. Really. This book shows you the significant data science techniques, how they work, how to use them, and how they bebefit your business, large or small".

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