Linear Algebra Full Course | Linear Algebra for newbies

What you will study
✓Operations on one matrix, together with fixing linear programs, and Gauss-Jordan elimination
✓Matrices as vectors, together with linear mixtures and span, linear independence, and subspaces
✓Matrix-vector merchandise, together with the null and column areas, and fixing Ax=b
✓Inverses, together with invertible and singular matrices, and fixing programs with inverse matrices
✓Transposes, together with their determinants, and the null (left null) and column (row) areas of the transpose
✓Orthonormal bases and Gram-Schmidt, together with definition of the orthonormal foundation, and changing to an orthonormal foundation with the Gram-Schmidt course of
✓Operations on two matrices, together with matrix multiplication and elimination matrices

This course was created by Dr. Linda Inexperienced, a lecturer on the College of North Carolina at Chapel Hill. Try her YouTube https://www.youtube.com/channel/UCkyLJh6hQS1TlhUZxOMjTFw

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00:03:38 Fixing Methods of Linear Equation
00:14:55 Utilizing Matrices to unravel Linear Equations
00:28:28 Decreased Row Echelon type
00:37:08 Gaussian Elimination
00:47:47 Existence and Uniqueness of Options
01:02:18 Linear Equations setup
01:09:31 Matrix Addition and Scalar Multiplication
01:19:13 Matrix Multiplication
01:31:28 Properties of Matrix Multiplication
01:38:58 Interpretation of matrix Multiplication
01:50:35 Introduction to Vectors
02:02:30 Fixing Vector Equations
02:15:59 Fixing Matrix Equations
02:24:20 Matrix Inverses
02:33:14 Matrix Inverses for two*2 Matrics
02:38:30 Equal Circumstances for a Matrix to be INvertible
02:45:34 Properties of Matrix INverses
02:56:06 Transpose
03:04:43 Symmetric and Skew-symmetric Matrices

03:13:54 Hint
03:23:01 The Determent of a Matrix
03:35:17 Determinant and Elementary Row Operations
03:47:28 Determinant Properties
03:58:54 Invertible Matrices and Their Determinants…..
04:04:23 Eigenvalues and Eigenvectors
04:20:55 Properties of Eigenvalues
04:32:03 Diagonalizing Matrices
04:45:16 Dot Product (linear Algebra )
04:49:41 Unit Vectors

04:54:41 Orthogonal Vectors
04:59:27 Orthogonal Matrices
05:07:06 Symmetric Matrices and Eigenvectors and Eigenvalues
05:12:05 Symmetric Matrices and Eigenvectors and Eigenvalues
05:18:17 Diagonalizing Symmetric Matrices
05:29:17 Linearly Impartial Vectors
05:36:44 Gram-Schmidt Orthogonalization
05:49:43 Singular Worth Decomposition Introduction
05:55:46 Singular Worth Decomposition The best way to Discover It
06:11:16 Singular Worth Decomposition Why it Works

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