Math for Machine Learning | C88A5932F52ACA8F7C5C272226F29ADC2132A81A

Math for Machine Learning

Name	Math for Machine Learning	DOWNLOAD Copy Link
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
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Visit Coursedrive.org.url	0.1 KB
Course Downloaded from coursedrive.org.txt	0.5 KB
Total files 77