[FreeCoursesOnline.Me] [Stone River eLearning] Math for Machine Learning - [FCO]

• [FreeCoursesOnline.Me] [Stone River eLearning] Math for Machine Learning - [FCO]
• 01.Course Promo.mp4 4.7 MB
• 02.Course Introduction.mp4 5.2 MB
• 03.Linear Regression.mp4 11 MB
• 04.The Least Squares Method.mp4 17.5 MB
• 05.Linear Algebra Solution to Least Squares Problem.mp4 17.9 MB
• 06.Example Linear Regression.mp4 6 MB
• 07.Summary Linear Regression.mp4 1.6 MB
• 08.Classification.mp4 1.7 MB
• 09.Linear Discriminant Analysis.mp4 967.1 KB
• 10.The Posterior Probability Functions.mp4 5.3 MB
• 11.Modelling the Posterior Probability Functions.mp4 11.3 MB
• 12.Linear Discriminant Functions.mp4 8.4 MB
• 13.Estimating the Linear Discriminant Functions.mp4 8.6 MB
• 14.Classifying Data Points Using Linear Discriminant Functions.mp4 4.9 MB
• 15.LDA Example 1.mp4 20.2 MB
• 16.LDA Example 2.mp4 26.9 MB
• 17.Summary Linear Discriminant Analysis.mp4 4.8 MB
• 18.Logistic Regression.mp4 1.6 MB
• 19.Logistic Regression Model of the Posterior Probability Function.mp4 4.2 MB
• 20.Estimating the Posterior Probability Function.mp4 12.9 MB
• 21.The Multivariate Newton-Raphson Method.mp4 16.6 MB
• 22.Maximizing the Log-Likelihood Function.mp4 21.4 MB
• 23.Logistic Regression Example.mp4 14.3 MB
• 24.Summary Logistic Regression.mp4 3.7 MB
• 25.Artificial Neural Networks.mp4 778.6 KB
• 26.Neural Network Model of the Output Functions.mp4 18.8 MB
• 27.Forward Propagation.mp4 1.6 MB
• 28.Choosing Activation Functions.mp4 5.9 MB
• 29.Estimating the Output Functions.mp4 3 MB
• 30.Error Function for Regression.mp4 3.3 MB
• 31.Error Function for Binary Classification.mp4 8.1 MB
• 32.Error Function for Multiclass Classification.mp4 6.3 MB
• 33.Minimizing the Error Function Using Gradient Descent.mp4 9.2 MB
• 34.Backpropagation Equations.mp4 6.1 MB
• 35.Summary of Backpropagation.mp4 2.3 MB
• 36.Summary Artificial Neural Networks.mp4 5 MB
• 37.Maximal Margin Classifier.mp4 3.1 MB
• 38.Definitions of Separating Hyperplane and Margin.mp4 8.4 MB
• 39.Proof 1.mp4 10.8 MB
• 40.Maximizing the Margin.mp4 5.3 MB
• 41.Definition of Maximal Margin Classifier.mp4 1.5 MB
• 42.Reformulating the Optimization Problem.mp4 12.2 MB
• 43.Proof 2.mp4 1.8 MB
• 44.Proof 3.mp4 7.3 MB
• 45.Proof 4.mp4 13 MB
• 46.Proof 5.mp4 8.1 MB
• 47.Solving the Convex Optimization Problem.mp4 1.7 MB
• 48.KKT Conditions.mp4 2.7 MB
• 49.Primal and Dual Problems.mp4 2.1 MB
• 50.Solving the Dual Problem.mp4 4.8 MB
• 51.The Coefficients for the Maximal Margin Hyperplane.mp4 677 KB
• 52.The Support Vectors.mp4 1.3 MB
• 53.Classifying Test Points.mp4 2.5 MB
• 54.Maximal Margin Classifier Example 1.mp4 14.4 MB
• 55.Maximal Margin Classifier Example 2.mp4 16.7 MB
• 56.Summary Maximal Margin Classifier.mp4 1.6 MB
• 57.Support Vector Classifier.mp4 5.3 MB
• 58.Slack Variables Points on Correct Side of Hyperplane.mp4 5.5 MB
• 59.Slack Variables Points on Wrong Side of Hyperplane.mp4 2.2 MB
• 60.Formulating the Optimization Problem.mp4 5.5 MB
• 61.Definition of Support Vector Classifier.mp4 1.2 MB
• 62.A Convex Optimization Problem.mp4 3.3 MB
• 63.Solving the Convex Optimization Problem (Soft Margin).mp4 9.4 MB
• 64.The Coefficients for the Soft Margin Hyperplane.mp4 2.9 MB
• 65.Classifying Test Points (Soft Margin).mp4 2.4 MB
• 66.The Support Vectors (Soft Margin).mp4 2.3 MB
• 67.Support Vector Classifier Example 1.mp4 22.1 MB
• 68.Support Vector Classifier Example 2.mp4 14.3 MB
• 69.Summary Support Vector Classifier.mp4 1.9 MB
• 70.Support Vector Machine Classifier.mp4 1.7 MB
• 71.Enlarging the Feature Space.mp4 8.2 MB
• 72.The Kernel Trick.mp4 6.9 MB
• 73.Summary Support Vector Machine Classifier.mp4 3.4 MB
• Discuss.FreeTutorials.Us.html 165.7 KB
• FreeCoursesOnline.Me.html 108.3 KB
• FreeTutorials.Eu.html 102.2 KB
• How you can help Team-FTU.txt 259 B

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