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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.
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
Anonymous
Posted Sun Feb 09 00:00:00 EST 2014
When trying to learn about a new field, one of the most common difficulties is to find books (and other materials) that have the right "depth". All too often one ends up with either a friendly but largely useless book that oversimplifies or a heavy academic tome that, though authoritative and comprehensive, is condemned to sit gathering dust in one's shelves. "Data Science for Business" gets it just right.
What I mean might become clearer if I point out what this book is *not*:
- It is *not* a computer science textbook with a focus on theoretical derivations and algorithms.
- It is *not* a "cookbook" that provides "step-by-step" guidance with little to no explanation of what one is doing.
- It is *not* your standard "management" title on the cool tech du jour available at airport stands and meant to be read in one sitting (buzzwords, hype and overly enthusiastic statements making up for the dearth of actual content).
Instead, it is close to being the perfect guide for the intelligent reader who -- regardless of whether s/he has a tech background -- has a sincere desire to learn how the tools and principles of data science can be used to extract meaningful information from huge datasets. Highly recommended.
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Overview
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 ...