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Sl.No Chapter Name MP4 Download Transcript Download
1The human brainDownloadPDF unavailable
2Introduction to Neural NetworksDownloadPDF unavailable
3Models of a neuronDownloadPDF unavailable
4Feedback and network architecturesDownloadPDF unavailable
5Knowledge representationDownloadPDF unavailable
6Prior information and invariancesDownloadPDF unavailable
7Learning processesDownloadPDF unavailable
8Perceptron 1DownloadPDF unavailable
9Perceptron 2DownloadPDF unavailable
10Batch perceptron algorithmDownloadPDF unavailable
11Perceptron and Bayes classifierDownloadPDF unavailable
12Linear regression 1DownloadPDF unavailable
13Linear regression 2DownloadPDF unavailable
14Linear regression 3DownloadPDF unavailable
15Logistic regressionDownloadPDF unavailable
16Multi-layer perceptron 1DownloadPDF unavailable
17Multi-layer perceptron 2DownloadPDF unavailable
18Back propagation 1DownloadPDF unavailable
19Back propagation 2DownloadPDF unavailable
20XOR problemDownloadPDF unavailable
21Universal approximation functionDownloadPDF unavailable
22Complexity Regularization and Cross validationDownloadPDF unavailable
23Convolutional Neural Networks (CNN)DownloadPDF unavailable
24Cover’s TheoremDownloadPDF unavailable
25Multivariate interpolation problemDownloadPDF unavailable
26Radial basis functions (RBF)DownloadPDF unavailable
27Recursive least squares algorithmDownloadPDF unavailable
28Comparison of RBF with MLPDownloadPDF unavailable
29Kernel regression using RBFsDownloadPDF unavailable
30Kernel FunctionsDownloadPDF unavailable
31Basics of constrained optimizationDownloadPDF unavailable
32Optimization with equality constraintDownloadPDF unavailable
33Optimization with inequality constraintDownloadPDF unavailable
34Support Vector Machines (SVM)DownloadPDF unavailable
35Optimal hyperplane for linearly separable patternsDownloadPDF unavailable
36Quadratic optimization for finding optimal hyperplaneDownloadPDF unavailable
37Optimal hyperplane for non-linearly separable patternsDownloadPDF unavailable
38Inner product kernel and Mercer’s theoremDownloadPDF unavailable
39Optimal design of an SVMDownloadPDF unavailable
40ε-insensitive loss functionDownloadPDF unavailable
41XOR problem revisited using SVMsDownloadPDF unavailable
42Hilbert SpaceDownloadPDF unavailable
43Reproducing Kernel Hilbert SpaceDownloadPDF unavailable
44Representer TheoremDownloadPDF unavailable
45Generalized applicability of the representer theoremDownloadPDF unavailable
46Regularization TheoryDownloadPDF unavailable
47Euler-Lagrange EquationDownloadPDF unavailable
48Regularization NetworksDownloadPDF unavailable
49Generalized RBF networksDownloadPDF unavailable
50XOR problem revisited using RBFDownloadPDF unavailable
51Structural Risk MinimizationDownloadPDF unavailable
52Bias-Variance DilemmaDownloadPDF unavailable
53Estimation of regularization parametersDownloadPDF unavailable
54Basics of L1 regularizationDownloadPDF unavailable
55GraftingDownloadPDF unavailable
56Kernel PCADownloadPDF unavailable
57Hebbian based maximum eigen filter -1DownloadPDF unavailable
58Hebbian based maximum eigen filter -2DownloadPDF unavailable
59Hebbian based maximum eigen filter - 3DownloadPDF unavailable
60VC dimensionDownloadPDF unavailable
61AutoencodersDownloadPDF unavailable
62Denoising AutoencodersDownloadPDF unavailable
63Demo – PerceptronDownloadPDF unavailable
64Demo – Motivation for CNNDownloadPDF unavailable
65Back propagation in Convolutional Neural NetworkDownloadPDF unavailable
66Ethics in AI research and coverage summaryDownloadPDF unavailable