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Math for Machine Learning

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Math for Machine Learning

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Total Size

599.0 MB

Total Files

77

Hash

C88A5932F52ACA8F7C5C272226F29ADC2132A81A

/Math for Machine Learning/

16 - LDA Example 2.mp4

31.0 MB

01 - Course Promo.mp4

5.7 MB

02 - Course Introduction.mp4

6.3 MB

03 - Linear Regression.mp4

12.7 MB

04 - The Least Squares Method.mp4

20.2 MB

05 - Linear Algebra Solution to Least Squares Problem.mp4

20.8 MB

06 - Example Linear Regression.mp4

6.9 MB

07 - Summary Linear Regression.mp4

1.9 MB

08 - Classification.mp4

1.7 MB

09 - Linear Discriminant Analysis.mp4

990.3 KB

10 - The Posterior Probability Functions.mp4

6.1 MB

11 - Modelling the Posterior Probability Functions.mp4

13.1 MB

12 - Linear Discriminant Functions.mp4

9.7 MB

13 - Estimating the Linear Discriminant Functions.mp4

10.0 MB

14 - Classifying Data Points Using Linear Discriminant Functions.mp4

5.7 MB

15 - LDA Example 1.mp4

23.3 MB

17 - Summary Linear Discriminant Analysis.mp4

5.6 MB

18 - Logistic Regression.mp4

1.7 MB

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

4.4 MB

20 - Estimating the Posterior Probability Function.mp4

13.5 MB

21 - The Multivariate Newton-Raphson Method.mp4

18.9 MB

22 - Maximizing the Log-Likelihood Function.mp4

24.6 MB

23 - Logistic Regression Example.mp4

16.5 MB

24 - Summary Logistic Regression.mp4

4.4 MB

25 - Artificial Neural Networks.mp4

797.2 KB

26 - Neural Network Model of the Output Functions.mp4

21.7 MB

27 - Forward Propagation.mp4

1.8 MB

28 - Choosing Activation Functions.mp4

6.9 MB

29 - Estimating the Output Functions.mp4

3.5 MB

30 - Error Function for Regression.mp4

3.5 MB

31 - Error Function for Binary Classification.mp4

9.5 MB

32 - Error Function for Multiclass Classification.mp4

6.6 MB

33 - Minimizing the Error Function Using Gradient Descent.mp4

10.7 MB

34 - Backpropagation Equations.mp4

7.1 MB

35 - Summary of Backpropagation.mp4

2.7 MB

36 - Summary Artificial Neural Networks.mp4

5.9 MB

37 - Maximal Margin Classifier.mp4

3.7 MB

38 - Definitions of Separating Hyperplane and Margin.mp4

9.8 MB

39 - Proof 1.mp4

12.4 MB

40 - Maximizing the Margin.mp4

6.2 MB

41 - Definition of Maximal Margin Classifier.mp4

1.8 MB

42 - Reformulating the Optimization Problem.mp4

14.0 MB

43 - Proof 2.mp4

2.1 MB

44 - Proof 3.mp4

8.4 MB

45 - Proof 4.mp4

15.0 MB

46 - Proof 5.mp4

9.4 MB

47 - Solving the Convex Optimization Problem.mp4

1.9 MB

48 - KKT Conditions.mp4

3.1 MB

49 - Primal and Dual Problems.mp4

2.2 MB

50 - Solving the Dual Problem.mp4

5.6 MB

51 - The Coefficients for the Maximal Margin Hyperplane.mp4

784.3 KB

52 - The Support Vectors.mp4

1.6 MB

53 - Classifying Test Points.mp4

2.9 MB

54 - Maximal Margin Classifier Example 1.mp4

16.6 MB

55 - Maximal Margin Classifier Example 2.mp4

19.4 MB

56 - Summary Maximal Margin Classifier.mp4

1.8 MB

57 - Support Vector Classifier.mp4

6.2 MB

58 - Slack Variables Points on Correct Side of Hyperplane.mp4

6.3 MB

59 - Slack Variables Points on Wrong Side of Hyperplane.mp4

2.5 MB

60 - Formulating the Optimization Problem.mp4

6.3 MB

61 - Definition of Support Vector Classifier.mp4

1.3 MB

62 - A Convex Optimization Problem.mp4

3.8 MB

63 - Solving the Convex Optimization Problem (Soft Margin).mp4

10.9 MB

64 - The Coefficients for the Soft Margin Hyperplane.mp4

3.4 MB

65 - Classifying Test Points (Soft Margin).mp4

2.8 MB

66 - The Support Vectors (Soft Margin).mp4

2.7 MB

67 - Support Vector Classifier Example 1.mp4

25.5 MB

68 - Support Vector Classifier Example 2.mp4

16.5 MB

69 - Summary Support Vector Classifier.mp4

2.3 MB

70 - Support Vector Machine Classifier.mp4

2.0 MB

71 - Enlarging the Feature Space.mp4

9.5 MB

72 - The Kernel Trick.mp4

7.9 MB

73 - Summary Support Vector Machine Classifier.mp4

4.0 MB

ReadMe.txt

0.5 KB

Visit Coursedrive.org.url

0.1 KB

/

Visit Coursedrive.org.url

0.1 KB

Course Downloaded from coursedrive.org.txt

0.5 KB

 

Total files 77


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