000			00352nam a2200145 4500
999			_c111500 _d111500
003			OSt
005			20180720142316.0
008			180404b xxu||||| |||| 00| 0 eng d
020			_a9781119092940
040			_c
082			_a005.74 _bCAD
100			_aCady, Field _926366
245			_aThe Data Science Handbook
260			_bJohn and Wiley Sons, Inc. _c2017 _aHoboken
300			_a396p
500			_a1. Introduction: Becoming a Unicorn Part 1 The Stuff You'll Always Use 2. The Data Science Road Map 3. Programming Languages 4. Data Munging: String Manipulation, Regular Expressions, and Data Cleaning 5. Visualizations and Simple Metrics 6. Machine Learning Overview 7. Interlude: Feature Extraction Ideas 8. Machine Learning Classification 9. Technical Communication and Documentation Part II Stuff You Still Need to Know 10. Unsupervised Learning: Clustering and Dimensionality Reduction 11. Regression 12. Data Encodings and File Formats 13. Big Data 14. Databases 15. Software Engineering Best Practices 16. Natural Language Processing 17. Time Series Analysis 18. Probability 19. Statistics 20. Programming Language Concepts 21. Performance and Computer Memory Part III Specialized or Advanced Topics 22. Computer Memory and Data Structures 23. Maximum Likelihood Estimation and Optimization 24. Advanced Classifiers 25. Stochastic Modeling
600			_aStatistics - Data processing - Handbooks, manuals _929801
942			_2ddc _cLB _k005.74 _mCAD