Data science from scratch: first principles with Python/
xvii, 384 p. : graphs, illustration; 23 cm. Content notes : 1. 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. Deep learning -- 20. Clustering -- 21. Natural language processing -- 22. Network analysis -- 23. Recommender systems -- 24. Databases and SQL -- 25. MapReduce -- 26. Data ethics -- 27. Go forth and do data science -- Index Data Science Python
