Sl.No Chapter Name MP4 Download
1Basics of Linear Algebra: Linear IndependenceDownload
2Linear Algebra: Rank of a matrixDownload
3Linear Algebra - Subspaces of a matrix -1Download
4Linear Algebra - Subspaces of a matrix -2Download
5Linear Algebra -- Null spaceDownload
6Linear Algebra -- Eigen Vectors/Values of a matrix -1Download
7Linear Algebra -- Eigen Vectors/Values of a matrix -2Download
8Programming Eigen Decomposition using PythonDownload
9Singular Value Decomposition - 1Download
10Singular Value Decomposition - 2Download
11Principal Component Analysis - 1Download
12Principal Component Analysis - 2Download
13Principal Component Analysis - 3Download
14Principal Component Analysis - CodingDownload
15Machine Learning - OverviewDownload
16Optimisation ProblemsDownload
17Gradient of a Vector Valued Function -1Download
18Gradient of a Vector Valued Function -2Download
19Neural Netowrks - OverviewDownload
20Neural Netowrks - BackpropagationDownload
21Optimisation - Introduction to optimisation problemsDownload
22Optimisation - Relaxation and approximate convergenceDownload
23Optimisation - First Order Optimality ConditionDownload
24Optimisation - Second Order Optimality ConditionDownload
25Proof of Second Order Optimality Condition, Gradient MethodsDownload
26Gradient Descent -2Download
27Variants of Gradient Descent -1Download
28Variants of Gradient Descent -2Download
29Variants of Gradient Descent -3Download
30Convex SetsDownload
31Convex FunctionsDownload
32Duality and Lagrangian - Part 1Download
33Duality and Lagrangian - Part 2Download
34Duality and Lagrangian - Part 3Download
35Coding: Introduction to PytorchDownload
36Guest Lecture: Support Vector MachineDownload

Sl.No Chapter Name English
1Basics of Linear Algebra: Linear IndependencePDF unavailable
2Linear Algebra: Rank of a matrixPDF unavailable
3Linear Algebra - Subspaces of a matrix -1PDF unavailable
4Linear Algebra - Subspaces of a matrix -2PDF unavailable
5Linear Algebra -- Null spacePDF unavailable
6Linear Algebra -- Eigen Vectors/Values of a matrix -1PDF unavailable
7Linear Algebra -- Eigen Vectors/Values of a matrix -2PDF unavailable
8Programming Eigen Decomposition using PythonPDF unavailable
9Singular Value Decomposition - 1PDF unavailable
10Singular Value Decomposition - 2PDF unavailable
11Principal Component Analysis - 1PDF unavailable
12Principal Component Analysis - 2PDF unavailable
13Principal Component Analysis - 3PDF unavailable
14Principal Component Analysis - CodingPDF unavailable
15Machine Learning - OverviewPDF unavailable
16Optimisation ProblemsPDF unavailable
17Gradient of a Vector Valued Function -1PDF unavailable
18Gradient of a Vector Valued Function -2PDF unavailable
19Neural Netowrks - OverviewPDF unavailable
20Neural Netowrks - BackpropagationPDF unavailable
21Optimisation - Introduction to optimisation problemsPDF unavailable
22Optimisation - Relaxation and approximate convergencePDF unavailable
23Optimisation - First Order Optimality ConditionPDF unavailable
24Optimisation - Second Order Optimality ConditionPDF unavailable
25Proof of Second Order Optimality Condition, Gradient MethodsPDF unavailable
26Gradient Descent -2PDF unavailable
27Variants of Gradient Descent -1PDF unavailable
28Variants of Gradient Descent -2PDF unavailable
29Variants of Gradient Descent -3PDF unavailable
30Convex SetsPDF unavailable
31Convex FunctionsPDF unavailable
32Duality and Lagrangian - Part 1PDF unavailable
33Duality and Lagrangian - Part 2PDF unavailable
34Duality and Lagrangian - Part 3PDF unavailable
35Coding: Introduction to PytorchPDF unavailable
36Guest Lecture: Support Vector MachinePDF unavailable

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2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available