Data Science for Business : What You Need to Know About Data Mining and Data-Analytic Thinking.
2013
386
212.68-PROVO
ANALYSE DES DONNEES ; ALGORITHME ; MATHEMATIQUES ; STATISTIQUE ; ANALYSE QUANTITATIVE
N° | Cote | Code barre | Commentaire | |
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1 | [disponible] | |||
2 | [disponible] |
ISBN 13 : 978-1-449-36132-7
Sommaire :
Praise
Dedication
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
C. Bibliography
Index
Langue : Anglais
Localisation : Bibliothèque Campus de Nice
Support : Papier
Etat : Présent
Propriétaire : Bibliothèque