Data Science for Business What You Need to Know About Data Mining and Data-Analytic Thinking pdf RUPOM

Data Science for Business (2013)

TRUE PDF WITH BOOKMARKS & INDEX



Authors:
Foster Provost
Tom Fawcett
Publisher: O'Reilly Media
Language : English
Pages: 409
Reader Required: Adobe Reader, Foxit, Nitro etc.
Published : August 19, 2013
ISBN: 978-1449361327

Contents:
Chapter 01. Introduction: Data-Analytic Thinking
Chapter 02. Business Problems and Data Science Solutions
Chapter 03. Introduction to Predictive Modeling: From Correlation to Supervised Segmentation
Chapter 04. Fitting a Model to Data
Chapter 05. Overfitting and Its Avoidance
Chapter 06. Similarity, Neighbors, and Clusters
Chapter 07. Decision Analytic Thinking I: What Is a Good Model?
Chapter 08. Visualizing Model Performance
Chapter 09. 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
Chapter 15. Embedded Machine Learning
APPENDIX A. Proposal Review Guide
APPENDIX B. Another Sample Proposal
Glossary
Bibliography
Index
About the Authors