2. Introduction

5. Before Learning I’m learning, hence I need adapt!

6. After Result: Liony adjusts his diet.

9. Motivation

14. Important Problems

15. Clustering

16. Classification x1 x2

19. Classification

20. Regression

22. Learning Issues

25. Segmentation

26. Color Space RGB space RGB space

27. Color Space (cont)

28. Suitable Clustering

31. Learning Ability over fitting

32. Problems with Over-fitting

33. SVM vs Decision Trees

36. Training a Network

37. Non-trivial Functions

38. Optimization

41. Gradient Descent

42. Problem: Local Extrema

43. Problem: Speed

44. Linear Programming x1 x2 lines define a convex function planes in 3D etc

46. Open Problems

49. The end Questions?

52. Naive Bayes good spam write people free π π No. Good No. Spam * *

53. Graph Clustering

54. Mean Shift

57. Solution Stability y-shift slope

58. Some Issues with Model Selection normal outliers wrong model

59. Real Photo in Color Space EM KMeans

60. Conjugate Gradient

61. Newton’s Method