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| 100 |
_aProvost, Foster _946121 |
||
| 245 | _aData Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking | ||
| 260 |
_bShroff Publishers & Distributors Pvt. Ltd. _c2013 _aSebastopol |
||
| 300 | _a384p | ||
| 500 | _a1. Introduction: Data-Analytic Thinking 2. Business Problems and Data Science Solutions 3. Introduction to Predictive Modeling: From Correlation to Supervised Segmentation 4. Fitting a Model to Data 5. Overfitting and Its Avoidance 6. Similarity, Neighbors, and Clusters 7. Decision Analytic Thinking I: What Is a Good Model? 8. Visualizing Model Performance 9. Evidence and Probabilities 10. Representing and Mining Text 11. Decision Analytic Thinking II: Toward Analytical Engineering 12. Other Data Science Tasks and Techniques 13. Data Science and Business Strategy 14. Conclusion | ||
| 600 |
_aBig data - Information science _946122 |
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| 700 |
_aFawcett, Tom _946123 |
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_2ddc _cLB _k005.74 _mPRO |
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