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Showing below up to 50 results in range #1 to #50.

1. Main Page‏‎ (17:11, 24 May 2014)
2. Overfitting‏‎ (15:42, 7 June 2014)
3. Model parameter‏‎ (16:31, 7 June 2014)
4. Hyperparameter‏‎ (16:42, 7 June 2014)
5. Second-order iterative learning algorithm‏‎ (23:15, 18 June 2014)
6. Random initialization‏‎ (23:47, 18 June 2014)
7. Training set‏‎ (23:53, 18 June 2014)
8. First-order iterative learning algorithm‏‎ (23:57, 18 June 2014)
9. Learning curve for number of iterations‏‎ (02:17, 19 June 2014)
10. Lazy learning‏‎ (16:53, 22 June 2014)
11. Feature‏‎ (17:07, 25 June 2014)
12. Cross-validation set‏‎ (02:32, 26 July 2014)
13. Learning curve‏‎ (03:53, 29 July 2014)
14. Machine learning terminology‏‎ (18:21, 15 August 2014)
15. Model selection‏‎ (18:24, 15 August 2014)
16. Generalization error‏‎ (23:21, 15 August 2014)
17. Learning algorithm‏‎ (23:25, 15 August 2014)
18. Learning algorithm hyperparameter‏‎ (00:38, 16 August 2014)
19. Gradient descent‏‎ (04:58, 16 August 2014)
20. Data matrix‏‎ (00:07, 28 September 2014)
21. Crossing of categorical variables‏‎ (03:34, 6 October 2014)
22. Position normalizer‏‎ (03:42, 6 October 2014)
23. Continuous encoding of categorical variables trick‏‎ (04:10, 6 October 2014)
24. Hyperparameter optimization‏‎ (16:46, 18 January 2015)
25. Model class selection‏‎ (20:06, 7 May 2016)
26. Feature selection‏‎ (01:05, 9 May 2016)
27. Linear regression‏‎ (15:37, 10 September 2017)
28. Regularization‏‎ (15:39, 10 September 2017)
29. Lasso‏‎ (16:25, 10 September 2017)
30. Cost function‏‎ (16:44, 10 September 2017)
31. Comparison of lasso and ridge regularization‏‎ (17:52, 10 September 2017)
32. Logistic regression‏‎ (20:13, 10 September 2017)
33. Sandbox‏‎ (20:15, 10 September 2017)
34. Comparison of machine learning textbooks‏‎ (02:06, 19 March 2018)
35. Causal inference‏‎ (16:57, 2 June 2018)
36. Derivative of a quadratic form‏‎ (03:23, 14 July 2018)
37. Backpropagation derivation using Leibniz notation‏‎ (00:26, 9 November 2018)
38. Backpropagation‏‎ (06:54, 7 January 2019)
39. Probability‏‎ (00:24, 15 January 2019)
40. Methods of discovering causal effects‏‎ (00:25, 15 January 2019)
41. Reverse regression‏‎ (00:25, 15 January 2019)
42. Collider‏‎ (00:26, 15 January 2019)
43. V-structure‏‎ (00:26, 15 January 2019)
44. List of sample space perspectives‏‎ (14:52, 15 January 2019)
45. Disappearance of sample space‏‎ (22:08, 15 January 2019)
46. Covariance matrix‏‎ (03:40, 16 January 2019)
47. Back-door path‏‎ (04:35, 16 January 2019)
48. Do operator‏‎ (23:11, 14 February 2019)
49. Recognizing Simpson's paradox‏‎ (07:22, 17 February 2019)
50. Equivalence of random coinflips view and minimal programs view‏‎ (17:42, 17 April 2019)