000			01031nam a22001577a 4500
999			_c5008 _d5008
008			180803b ||||| |||| 00| 0 eng d
020			_a978-93-5213-096-2
082			_223 _a519.502855133 _bGRU
100			_aGrus Joel
245			_aData Science from scratch : _bFirst principles with python / _cJoel Grus.
250			_b2018.
260			_aNew Delhi. _bShroff Publishers & Distributors; _c2018.
300			_a311 p . ; _bsoftbound _c17x23cm
505			_a1. Introduction 2. A crash course in python 3. Visualizing data 4. Linear Algebra 5. Statistics 6. Probability 7. Hypothesis and inference 8. Gradient Descent 9. Getting Data 10. Working with data 11. Machine learning 12. K-nearest neighbors 13. Naive Bayes 14. Simple linear regression 15. Multiple regression 16. Logistic regression 17. Decision trees 18. Neural networks 19. Clustering 20. Natural language processing 21. Network Analysis 22. Recommender systems 23. Databases and SQL 24. Mapreduce 25. Go forth and do data science
942			_2ddc _cBK