
Data Science for Business
What you need to know about data mining and data-analytic thinking
O'Reilly (Publisher)
1st Edition
Published on 17. September 2013
Book
Paperback/Softback
413 pages
978-1-4493-6132-7 (ISBN)
Description
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces 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. This guide also helps you understand the many data-mining techniques in use today.
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company's data science projects. You'll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.
* Understand how data science fits in your organization-and how you can use it for competitive advantage
* Treat data as a business asset that requires careful investment if you're to gain real value
* Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way
* Learn general concepts for actually extracting knowledge from data
* Apply data science principles when interviewing data science job candidates
More details
Language
English
Place of publication
Sebastopol
United States
Target group
Professional and scholarly
Dimensions
Height: 233 mm
Width: 179 mm
Thickness: 26 mm
Weight
721 gr
ISBN-13
978-1-4493-6132-7 (9781449361327)
Schweitzer Classification
Other editions
Additional editions

Foster Provost
Data Science for Business
What You Need to Know about Data Mining and Data-Analytic Thinking
E-Book
07/2013
O'Reilly
€39.99
Available for download

Foster Provost
Data Science for Business
What You Need to Know about Data Mining and Data-Analytic Thinking
E-Book
07/2013
O'Reilly
€27.49
Available for download
Persons
Foster Provost is a Professor and NEC Faculty Fellow at the NYU Stern School of Business, where he has taught data science to MBAs for 15 years. His research and teaching focus on data science, machine learning, business analytics, (social) network data, and crowd-sourcing for data analytics. Tom Fawcett has a Ph.D. in machine learning from UMass-Amherst and has worked in industrial research (GTE Laboratories, NYNEX/Verizon Labs, HP Labs, etc.). He has served as action editor of the Machine Learning journal, before which he was an editorial board member.
Content
- 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