Modules / Lectures
Module NameDownload

Sl.No Chapter Name MP4 Download
1The human brainDownload
2Introduction to Neural NetworksDownload
3Models of a neuronDownload
4Feedback and network architecturesDownload
5Knowledge representationDownload
6Prior information and invariancesDownload
7Learning processesDownload
8Perceptron 1Download
9Perceptron 2Download
10Batch perceptron algorithmDownload
11Perceptron and Bayes classifierDownload
12Linear regression 1Download
13Linear regression 2Download
14Linear regression 3Download
15Logistic regressionDownload
16Multi-layer perceptron 1Download
17Multi-layer perceptron 2Download
18Back propagation 1Download
19Back propagation 2Download
20XOR problemDownload
21Universal approximation functionDownload
22Complexity Regularization and Cross validationDownload
23Convolutional Neural Networks (CNN)Download
24Cover’s TheoremDownload
25Multivariate interpolation problemDownload
26Radial basis functions (RBF)Download
27Recursive least squares algorithmDownload
28Comparison of RBF with MLPDownload
29Kernel regression using RBFsDownload
30Kernel FunctionsDownload
31Basics of constrained optimizationDownload
32Optimization with equality constraintDownload
33Optimization with inequality constraintDownload
34Support Vector Machines (SVM)Download
35Optimal hyperplane for linearly separable patternsDownload
36Quadratic optimization for finding optimal hyperplaneDownload
37Optimal hyperplane for non-linearly separable patternsDownload
38Inner product kernel and Mercer’s theoremDownload
39Optimal design of an SVMDownload
40ε-insensitive loss functionDownload
41XOR problem revisited using SVMsDownload
42Hilbert SpaceDownload
43Reproducing Kernel Hilbert SpaceDownload
44Representer TheoremDownload
45Generalized applicability of the representer theoremDownload
46Regularization TheoryDownload
47Euler-Lagrange EquationDownload
48Regularization NetworksDownload
49Generalized RBF networksDownload
50XOR problem revisited using RBFDownload
51Structural Risk MinimizationDownload
52Bias-Variance DilemmaDownload
53Estimation of regularization parametersDownload
54Basics of L1 regularizationDownload
56Kernel PCADownload
57Hebbian based maximum eigen filter -1Download
58Hebbian based maximum eigen filter -2Download
59Hebbian based maximum eigen filter - 3Download
60VC dimensionDownload
62Denoising AutoencodersDownload
63Demo – PerceptronDownload
64Demo – Motivation for CNNDownload
65Back propagation in Convolutional Neural NetworkDownload
66Ethics in AI research and coverage summaryDownload

Sl.No Chapter Name English
1The human brainDownload
To be verified
2Introduction to Neural NetworksDownload
To be verified
3Models of a neuronDownload
To be verified
4Feedback and network architecturesDownload
To be verified
5Knowledge representationDownload
To be verified
6Prior information and invariancesDownload
To be verified
7Learning processesDownload
To be verified
8Perceptron 1Download
To be verified
9Perceptron 2Download
To be verified
10Batch perceptron algorithmDownload
To be verified
11Perceptron and Bayes classifierDownload
To be verified
12Linear regression 1Download
To be verified
13Linear regression 2Download
To be verified
14Linear regression 3Download
To be verified
15Logistic regressionDownload
To be verified
16Multi-layer perceptron 1Download
To be verified
17Multi-layer perceptron 2PDF unavailable
18Back propagation 1PDF unavailable
19Back propagation 2PDF unavailable
20XOR problemPDF unavailable
21Universal approximation functionPDF unavailable
22Complexity Regularization and Cross validationPDF unavailable
23Convolutional Neural Networks (CNN)PDF unavailable
24Cover’s TheoremPDF unavailable
25Multivariate interpolation problemPDF unavailable
26Radial basis functions (RBF)PDF unavailable
27Recursive least squares algorithmPDF unavailable
28Comparison of RBF with MLPPDF unavailable
29Kernel regression using RBFsPDF unavailable
30Kernel FunctionsPDF unavailable
31Basics of constrained optimizationPDF unavailable
32Optimization with equality constraintPDF unavailable
33Optimization with inequality constraintPDF unavailable
34Support Vector Machines (SVM)PDF unavailable
35Optimal hyperplane for linearly separable patternsPDF unavailable
36Quadratic optimization for finding optimal hyperplanePDF unavailable
37Optimal hyperplane for non-linearly separable patternsPDF unavailable
38Inner product kernel and Mercer’s theoremPDF unavailable
39Optimal design of an SVMPDF unavailable
40ε-insensitive loss functionPDF unavailable
41XOR problem revisited using SVMsPDF unavailable
42Hilbert SpacePDF unavailable
43Reproducing Kernel Hilbert SpacePDF unavailable
44Representer TheoremPDF unavailable
45Generalized applicability of the representer theoremPDF unavailable
46Regularization TheoryPDF unavailable
47Euler-Lagrange EquationPDF unavailable
48Regularization NetworksPDF unavailable
49Generalized RBF networksPDF unavailable
50XOR problem revisited using RBFPDF unavailable
51Structural Risk MinimizationPDF unavailable
52Bias-Variance DilemmaPDF unavailable
53Estimation of regularization parametersPDF unavailable
54Basics of L1 regularizationPDF unavailable
55GraftingPDF unavailable
56Kernel PCAPDF unavailable
57Hebbian based maximum eigen filter -1PDF unavailable
58Hebbian based maximum eigen filter -2PDF unavailable
59Hebbian based maximum eigen filter - 3PDF unavailable
60VC dimensionPDF unavailable
61AutoencodersPDF unavailable
62Denoising AutoencodersPDF unavailable
63Demo – PerceptronPDF unavailable
64Demo – Motivation for CNNPDF unavailable
65Back propagation in Convolutional Neural NetworkPDF unavailable
66Ethics in AI research and coverage summaryPDF unavailable

Sl.No Language Book link
1EnglishNot Available
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available