000			01412nam a2200229 a 4500
003			AR-LpUFIB
005			20250311170516.0
008			230201s2013 xxua r 000 0 eng d
020			_a9781449361327
024	8		_aDIF-M8481 _b8702 _zDIF007763
040			_aAR-LpUFIB _bspa _cAR-LpUFIB
100	1		_aProvost, Foster
245	1	0	_aData science for business : _bwhat you need to know about data mining and data-analytic thinking
260			_aSebastopol : _b O'Reilly Media, _c2013
300			_axxi, 386 p. : _bil.
500			_aIncluye índice y bibliografía.
505	0		_a Preface -- 1. 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 -- A. Proposal Review Guide -- B. Another Sample Proposal -- Glossary -- C. Bibliography -- Index
650		4	_aMINERÍA DE DATOS
653			_anegocios
700	1		_aFawcet, Tom
942			_cBK
999			_c57536 _d57536