4shared - Math for Machine Learning ng Pablo

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Patunayan na hindi ka robot

13:52

15 - LDA Example 1.mp4

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Pablo

01:50

53 - Classifying Test Points.mp4

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Pablo

00:44

09 - Linear Discriminant Analysis.mp4

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02:09

64 - The Coefficients for the Soft Margin Hyperplane.mp4

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Pablo

01:34

17 - Summary Linear Discriminant Analysis.mp4

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Pablo

00:36

25 - Artificial Neural Networks.mp4

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Pablo

06:42

39 - Proof 1.mp4

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08:57

20 - Estimating the Posterior Probability Function.mp4

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05:44

38 - Definitions of Separating Hyperplane and Margin.mp4

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00:31

56 - Summary Maximal Margin Classifier.mp4

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Pablo

11:41

55 - Maximal Margin Classifier Example 2.mp4

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Pablo

01:47

36 - Summary Artificial Neural Networks.mp4

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02:46

02 - Course Introduction.mp4

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11:25

04 - The Least Squares Method.mp4

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01:36

65 - Classifying Test Points (Soft Margin).mp4

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07:33

03 - Linear Regression.mp4

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00:44

61 - Definition of Support Vector Classifier.mp4

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17:38

16 - LDA Example 2.mp4

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Pablo

14:53

67 - Support Vector Classifier Example 1.mp4

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Pablo

09:55

23 - Logistic Regression Example.mp4

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04:52

44 - Proof 3.mp4

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01:46

62 - A Convex Optimization Problem.mp4

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03:42

10 - The Posterior Probability Functions.mp4

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Pablo

04:30

28 - Choosing Activation Functions.mp4

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03:02

19 - Logistic Regression Model of the Posterior Probability Function.mp4

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Pablo

09:19

68 - Support Vector Classifier Example 2.mp4

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Pablo

02:29

37 - Maximal Margin Classifier.mp4

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Pablo

01:13

43 - Proof 2.mp4

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01:01

41 - Definition of Maximal Margin Classifier.mp4

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Pablo

02:27

30 - Error Function for Regression.mp4

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Pablo