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> > 컴퓨터 일반도서 > Databases > Data Mining

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Data Science for Business: What you need to know about data mining and data-analytic thinking
출판사 : O\'Reilly Media
저 자 : Provost
ISBN : 9781449361327
발행일 : 2013-8
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 414
판매가격 : 37,000원
판매여부 : 재고확인요망
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   Data Science for Business: What you need to know about data mining and data-analytic thinking 목차
PraisePreface
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: ConclusionProposal Review GuideAnother Sample ProposalGlossaryBibliography
Index
Colophon
   도서 상세설명   

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

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