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Data Science for Business

What You Need to Know About Data Mining and Data-analytic Thinking
BuchKartoniert, Paperback
408 Seiten
Englisch
O'Reilly Mediaerschienen am17.09.20131st ed.
This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR51,00
E-BookPDFDRM AdobeE-Book
EUR40,99
E-BookEPUBDRM AdobeE-Book
EUR28,49

Produkt

KlappentextThis broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.
Details
ISBN/GTIN978-1-4493-6132-7
ProduktartBuch
EinbandartKartoniert, Paperback
Erscheinungsjahr2013
Erscheinungsdatum17.09.2013
Auflage1st ed.
Seiten408 Seiten
SpracheEnglisch
Gewicht680 g
Illustrationenw. figs.
Artikel-Nr.28986914

Inhalt/Kritik

Inhaltsverzeichnis
Praise
Preface
Chapter 1: Introduction: Data-Analytic Thinking
Chapter 2: Business Problems and Data Science Solutions
Chapter 3: Introduction to Predictive Modeling: From Correlation to Supervised Segmentation
Chapter 4: Fitting a Model to Data
Chapter 5: Overfitting and Its Avoidance
Chapter 6: Similarity, Neighbors, and Clusters
Chapter 7: Decision Analytic Thinking I: What Is a Good Model?
Chapter 8: Visualizing Model Performance
Chapter 9: Evidence and Probabilities
Chapter 10: Representing and Mining Text
Chapter 11: Decision Analytic Thinking II: Toward Analytical Engineering
Chapter 12: Other Data Science Tasks and Techniques
Chapter 13: Data Science and Business Strategy
Chapter 14: Conclusion
Proposal Review Guide
Another Sample Proposal
Glossary
Bibliography
Index
Colophon
mehr

Autor

Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing.Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standard reading in data science both on methodology (evaluating data mining results) and on applications (fraud detection and spam filtering).