[FreeCoursesOnline.Me] [Stone River eLearning] Math for Machine Learning - [FCO]
File List
- 16.LDA Example 2.mp4 26.9 MB
- 67.Support Vector Classifier Example 1.mp4 22.1 MB
- 22.Maximizing the Log-Likelihood Function.mp4 21.4 MB
- 15.LDA Example 1.mp4 20.2 MB
- 26.Neural Network Model of the Output Functions.mp4 18.8 MB
- 05.Linear Algebra Solution to Least Squares Problem.mp4 17.9 MB
- 04.The Least Squares Method.mp4 17.5 MB
- 55.Maximal Margin Classifier Example 2.mp4 16.7 MB
- 21.The Multivariate Newton-Raphson Method.mp4 16.6 MB
- 54.Maximal Margin Classifier Example 1.mp4 14.4 MB
- 68.Support Vector Classifier Example 2.mp4 14.3 MB
- 23.Logistic Regression Example.mp4 14.3 MB
- 45.Proof 4.mp4 13.0 MB
- 20.Estimating the Posterior Probability Function.mp4 12.9 MB
- 42.Reformulating the Optimization Problem.mp4 12.2 MB
- 11.Modelling the Posterior Probability Functions.mp4 11.3 MB
- 03.Linear Regression.mp4 11.0 MB
- 39.Proof 1.mp4 10.8 MB
- 63.Solving the Convex Optimization Problem (Soft Margin).mp4 9.4 MB
- 33.Minimizing the Error Function Using Gradient Descent.mp4 9.2 MB
- 13.Estimating the Linear Discriminant Functions.mp4 8.6 MB
- 38.Definitions of Separating Hyperplane and Margin.mp4 8.4 MB
- 12.Linear Discriminant Functions.mp4 8.4 MB
- 71.Enlarging the Feature Space.mp4 8.2 MB
- 31.Error Function for Binary Classification.mp4 8.1 MB
- 46.Proof 5.mp4 8.1 MB
- 44.Proof 3.mp4 7.3 MB
- 72.The Kernel Trick.mp4 6.9 MB
- 32.Error Function for Multiclass Classification.mp4 6.3 MB
- 34.Backpropagation Equations.mp4 6.1 MB
- 06.Example Linear Regression.mp4 6.0 MB
- 28.Choosing Activation Functions.mp4 5.9 MB
- 58.Slack Variables Points on Correct Side of Hyperplane.mp4 5.5 MB
- 60.Formulating the Optimization Problem.mp4 5.5 MB
- 57.Support Vector Classifier.mp4 5.3 MB
- 40.Maximizing the Margin.mp4 5.3 MB
- 10.The Posterior Probability Functions.mp4 5.3 MB
- 02.Course Introduction.mp4 5.2 MB
- 36.Summary Artificial Neural Networks.mp4 5.0 MB
- 14.Classifying Data Points Using Linear Discriminant Functions.mp4 4.9 MB
- 17.Summary Linear Discriminant Analysis.mp4 4.8 MB
- 50.Solving the Dual Problem.mp4 4.8 MB
- 01.Course Promo.mp4 4.7 MB
- 19.Logistic Regression Model of the Posterior Probability Function.mp4 4.2 MB
- 24.Summary Logistic Regression.mp4 3.7 MB
- 73.Summary Support Vector Machine Classifier.mp4 3.4 MB
- 30.Error Function for Regression.mp4 3.3 MB
- 62.A Convex Optimization Problem.mp4 3.3 MB
- 37.Maximal Margin Classifier.mp4 3.1 MB
- 29.Estimating the Output Functions.mp4 3.0 MB
- 64.The Coefficients for the Soft Margin Hyperplane.mp4 2.9 MB
- 48.KKT Conditions.mp4 2.7 MB
- 53.Classifying Test Points.mp4 2.5 MB
- 65.Classifying Test Points (Soft Margin).mp4 2.4 MB
- 66.The Support Vectors (Soft Margin).mp4 2.3 MB
- 35.Summary of Backpropagation.mp4 2.3 MB
- 59.Slack Variables Points on Wrong Side of Hyperplane.mp4 2.2 MB
- 49.Primal and Dual Problems.mp4 2.1 MB
- 69.Summary Support Vector Classifier.mp4 1.9 MB
- 43.Proof 2.mp4 1.8 MB
- 08.Classification.mp4 1.7 MB
- 70.Support Vector Machine Classifier.mp4 1.7 MB
- 47.Solving the Convex Optimization Problem.mp4 1.7 MB
- 18.Logistic Regression.mp4 1.6 MB
- 27.Forward Propagation.mp4 1.6 MB
- 07.Summary Linear Regression.mp4 1.6 MB
- 56.Summary Maximal Margin Classifier.mp4 1.6 MB
- 41.Definition of Maximal Margin Classifier.mp4 1.5 MB
- 52.The Support Vectors.mp4 1.3 MB
- 61.Definition of Support Vector Classifier.mp4 1.2 MB
- 09.Linear Discriminant Analysis.mp4 967.1 KB
- 25.Artificial Neural Networks.mp4 778.6 KB
- 51.The Coefficients for the Maximal Margin Hyperplane.mp4 677.0 KB
- Discuss.FreeTutorials.Us.html 165.7 KB
- FreeCoursesOnline.Me.html 108.3 KB
- FreeTutorials.Eu.html 102.2 KB
- [TGx]Downloaded from torrentgalaxy.org.txt 524 bytes
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