Data Science 101

Presentation at the Data Science 101 workshop at Orangescape.

Transcript

1. Data Science 101: insight, not numbers Ronojoy Adhikari The Institute of Mathematical Sciences Chennai, India Orangescape Chennai, India Wednesday, 30 September 15
2. The purpose of computing is insight, not numbers. Wednesday, 30 September 15
3. The purpose of computing is insight, not numbers. Wednesday, 30 September 15
4. The purpose of computing is insight, not numbers. Richard Hamming Wednesday, 30 September 15
5. What is the purpose of data science ? Wednesday, 30 September 15
6. What is the purpose of data science ? Insight, not numbers! Wednesday, 30 September 15
7. Data science Wednesday, 30 September 15
8. Wednesday, 30 September 15
9. Data Wednesday, 30 September 15
10. Data Domain knowledge Wednesday, 30 September 15
11. Data Domain knowledge Data curation Wednesday, 30 September 15
12. Data Domain knowledge Data curation Mathematical model Wednesday, 30 September 15
13. Data Domain knowledge Data curation Mathematical model A/B testing Wednesday, 30 September 15
14. Data Domain knowledge Data curation Mathematical model A/B testing Machine learning Wednesday, 30 September 15
15. Data Domain knowledge Data curation Mathematical model A/B testing Machine learning Machine inference Wednesday, 30 September 15
16. Data Domain knowledge Data curation Mathematical model A/B testing Machine learning Machine inference Value from data Wednesday, 30 September 15
17. 1. Problem or question ? Wednesday, 30 September 15
18. Wednesday, 30 September 15
19. Let the data speak for themselves! Ronald Fisher Wednesday, 30 September 15
20. Let the data speak for themselves! Ronald Fisher The data cannot speak for themselves; and they never have, in any real problem of inference. Edwin Jaynes Wednesday, 30 September 15
21. Classification Regression Clustering Dimensionality reduction Wednesday, 30 September 15
22. Classification Regression Clustering Dimensionality reduction predict class, given attributes Wednesday, 30 September 15
23. Classification Regression Clustering Dimensionality reduction predict class, given attributes Wednesday, 30 September 15
24. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values Wednesday, 30 September 15
25. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values Wednesday, 30 September 15
26. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values group similar things together Wednesday, 30 September 15
27. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values group similar things together Wednesday, 30 September 15
28. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values group similar things together keeping only the relevant variables Wednesday, 30 September 15
29. Classification Regression Clustering Dimensionality reduction predict class, given attributes predict values, given other values group similar things together keeping only the relevant variables Wednesday, 30 September 15
30. 3. Frame a hypothesis (mathematical models) Wednesday, 30 September 15
31. Bayesian Blackbox Frequentist Causal Wednesday, 30 September 15
32. Bayesian Blackbox Frequentist Causal probability is a state of knowledge Wednesday, 30 September 15
33. Bayesian Blackbox Frequentist Causal probability is a state of knowledge probability is a frequency Wednesday, 30 September 15
34. Bayesian Blackbox Frequentist Causal probability is a state of knowledge probability is a frequency Wednesday, 30 September 15
35. Bayesian Blackbox Frequentist Causal probability is a state of knowledge ML : toolbox for processing data probability is a frequency Wednesday, 30 September 15
36. Bayesian Blackbox Frequentist Causal probability is a state of knowledge ML : toolbox for processing data probability is a frequency Wednesday, 30 September 15
37. Bayesian Blackbox Frequentist Causal probability is a state of knowledge ML : toolbox for processing data ML : learning generative models of data probability is a frequency Wednesday, 30 September 15
38. Bayesian Blackbox Frequentist Causal probability is a state of knowledge ML : toolbox for processing data ML : learning generative models of data probability is a frequency Wednesday, 30 September 15
39. Wednesday, 30 September 15
40. Wednesday, 30 September 15
41. Wednesday, 30 September 15
42. We are building a causal learning and inference engine that will beat the current state-of-art! Wednesday, 30 September 15
43. We are building a causal learning and inference engine that will beat the current state-of-art! Thank you for your attention! Wednesday, 30 September 15