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Урок 1.
00:14:18
Welcome Message
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Урок 2.
00:19:12
Linear Algebra RoadMap 2024
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Урок 3.
00:09:03
Pre-Requisites Introduction
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Урок 4.
00:10:31
Refreshment - Norms & Euclidean Distance
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Урок 5.
00:04:14
Refreshment - Real Numbers and Vector Space
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Урок 6.
00:04:45
Refreshment - Cartesian Coordinate System & Unit Circle
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Урок 7.
00:13:24
Refreshment - Angles, Unit Circle and Trigonometry
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Урок 8.
00:05:25
Refreshment - Pythagorean Theorem & Orthogonality
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Урок 9.
00:02:28
Why these Pre-Requisites Matter
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Урок 10.
00:30:55
Module 2.1: Foundations of Vectors
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Урок 11.
00:56:53
Module 2.2: Special Vectors and Operations
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Урок 12.
00:25:06
Module 2.3: Part 1 - Scalar Multiplication
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Урок 13.
00:47:10
Module 2.3 Part 2 - Linear Combination and Unit Vectors
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Урок 14.
00:40:06
Module 2.3 Part 3 - Span of Vectors
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Урок 15.
00:31:53
Module 2.3: Part 4 - Linear Independence
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Урок 16.
01:29:45
Module 2.4: Dot Product, Cauchy-Schwarz Inequality and Its
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Урок 17.
00:16:50
Module 1: Foundations of Linear Systems and Matrices
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Урок 18.
00:30:01
Module 2: Introduction to Matrices
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Урок 19.
00:35:01
Module 3: Core Matrix Operations
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Урок 20.
00:47:23
Module 4: Part 1 Solving Linear Systems - Gaussian Reduction
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Урок 21.
01:07:47
Module 4: Part 2 Solving Linear Systems - Gaussian Reduction
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Урок 22.
01:10:00
Module 4: Part 3 Solving Linear Systems - Gaussian Reduction
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Урок 23.
00:53:47
Module 4: Part 4 Solving Linear Systems - Gaussian Reduction
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Урок 24.
00:56:31
Module 1: Algebraic Laws for Matrices
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Урок 25.
00:50:52
Module 2: Determinants and Their Properties
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Урок 26.
01:03:32
Module 3: Matrix Inverses and Identity Matrix
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Урок 27.
00:23:15
Module 4: Transpose of Matrices: Properties and Applications
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Урок 28.
00:35:39
Module 1: Part 1 Basis of Vector Space
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Урок 29.
00:41:12
Module 1: Part 2 Vector Projection and Calculation
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Урок 30.
00:36:53
Module 1: Part 3 Gram-Schmidt Process
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Урок 31.
00:14:39
Module 2: Special Matrices and Their Properties
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Урок 32.
00:27:03
Module 3: Matrix Factorization, Examples and Applications
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Урок 33.
00:42:52
Module 4: QR Decomposition Overview
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Урок 34.
01:16:31
Module 5: Eigenvalues, Eigenvectors, and Eigen Decomposition
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Урок 35.
00:58:23
Module 6: Singular Value Decomposition (SVD)