Long pages

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

1. (hist) ‎Solomonoff induction ‎[19,556 bytes]
2. (hist) ‎Logistic regression ‎[18,650 bytes]
3. (hist) ‎Backpropagation ‎[11,312 bytes]
4. (hist) ‎Variants of Solomonoff induction ‎[11,187 bytes]
5. (hist) ‎Continuous encoding of categorical variables trick ‎[10,945 bytes]
6. (hist) ‎Comparison of machine learning textbooks ‎[10,307 bytes]
7. (hist) ‎Equivalence of random coinflips view and minimal programs view ‎[10,236 bytes]
8. (hist) ‎Summary table of probability terms ‎[9,036 bytes]
9. (hist) ‎Bellman equation derivation ‎[8,271 bytes]
10. (hist) ‎Derivative of a quadratic form ‎[6,769 bytes]
11. (hist) ‎Feature selection ‎[6,534 bytes]
12. (hist) ‎Learning algorithm hyperparameter ‎[5,345 bytes]
13. (hist) ‎Machine learning ‎[5,118 bytes]
14. (hist) ‎Data matrix ‎[4,929 bytes]
15. (hist) ‎Backpropagation derivation using Leibniz notation ‎[4,908 bytes]
16. (hist) ‎Learning curve for number of iterations ‎[4,502 bytes]
17. (hist) ‎Disappearance of sample space ‎[4,422 bytes]
18. (hist) ‎Unsupervised learning ‎[4,418 bytes]
19. (hist) ‎Cost function ‎[4,264 bytes]
20. (hist) ‎Proportion of valid programs view of Solomonoff induction ‎[4,000 bytes]
21. (hist) ‎Infinitely often and almost always ‎[3,899 bytes]
22. (hist) ‎Learning curve ‎[3,868 bytes]
23. (hist) ‎Learning algorithm ‎[3,728 bytes]
24. (hist) ‎Creation of causal graphs ‎[3,710 bytes]
25. (hist) ‎Supervised learning ‎[3,687 bytes]
26. (hist) ‎Artificial neuron ‎[3,669 bytes]
27. (hist) ‎Translating informal probability statements to formal counterparts ‎[3,616 bytes]
28. (hist) ‎Crossing of categorical variables ‎[3,136 bytes]
29. (hist) ‎Model class selection ‎[3,135 bytes]
30. (hist) ‎Artificial neural network ‎[3,103 bytes]
31. (hist) ‎Regularization ‎[2,907 bytes]
32. (hist) ‎Regression ‎[2,739 bytes]
33. (hist) ‎Dimensionality reduction ‎[2,719 bytes]
34. (hist) ‎Variance ‎[2,419 bytes]
35. (hist) ‎Do operator ‎[2,417 bytes]
36. (hist) ‎Clustering ‎[2,396 bytes]
37. (hist) ‎Quantities defined for a random variable that depend only on the distribution ‎[2,388 bytes]
38. (hist) ‎Covariance ‎[2,232 bytes]
39. (hist) ‎Hierarchical clustering ‎[2,084 bytes]
40. (hist) ‎Abstracting sensory data in Solomonoff induction ‎[2,057 bytes]
41. (hist) ‎Feature ‎[2,038 bytes]
42. (hist) ‎Principal component analysis ‎[2,010 bytes]
43. (hist) ‎Lower semicomputable function ‎[1,857 bytes]
44. (hist) ‎Shattering ‎[1,805 bytes]
45. (hist) ‎Lasso ‎[1,728 bytes]
46. (hist) ‎Expectation ‎[1,719 bytes]
47. (hist) ‎Back-door path ‎[1,693 bytes]
48. (hist) ‎Gradient descent ‎[1,647 bytes]
49. (hist) ‎Machine learning terminology ‎[1,566 bytes]
50. (hist) ‎V-structure ‎[1,467 bytes]