linearly.ai
Lecture00: How Do Machines Learn?
Math Abstraction Turing Computation ML

Lecture00: How Do Machines Learn?

· 2 min read
Lecture01: Fundamentals
Vectors Dimensions Equations Dot Product

Lecture01: Fundamentals

· 1 min read
Lecture02: Matrices & Transformations
Matrices Transformations Singularity Numpy

Lecture02: Matrices & Transformations

· 1 min read
Lecture03: Matrices & Views & Numpy
Matrices Transformations Numpy Dimensions

Lecture03: Matrices & Views & Numpy

· 1 min read
Lecture04: Elimination, Inverse Matrices & Permutations
Elimination Matrix Operations Inverse

Lecture04: Elimination, Inverse Matrices & Permutations

· 1 min read
Lecture05: Unique Matrix Multiplication Methods
Matrix Multiplication Elimination Inverse Matrices

Lecture05: Unique Matrix Multiplication Methods

· 1 min read
Lecture06: CR & LU Decompositions
CR Decomposition LU Decomposition Invertibility

Lecture06: CR & LU Decompositions

· 1 min read
Lecture07: Vector Spaces Intro
Vector Spaces Subspaces Column-Spaces

Lecture07: Vector Spaces Intro

· 1 min read
Lecture7.5: Subspaces, Columnspace, Rowspace, Nullspace
Columnspace Null Space Rowspace

Lecture7.5: Subspaces, Columnspace, Rowspace, Nullspace

· 1 min read
Lecture08: Null Space, Rank, Basis
Subspaces Null Space Rank Basis

Lecture08: Null Space, Rank, Basis

· 1 min read
Lecture09: 4 fundamental subspaces & proof for dim(rowspace)=dim(colspace)
4-Subspaces Null Space Proof Basis

Lecture09: 4 fundamental subspaces & proof for dim(rowspace)=dim(colspace)

· 1 min read
Lecture10: Orthogonality of 4-subpaces
Orthogonality Projections 4-Subspaces

Lecture10: Orthogonality of 4-subpaces

· 1 min read
Lecture11: 4 subspaces & transformations + transformers
Subspaces Transformations Transformers LSQ

Lecture11: 4 subspaces & transformations + transformers

· 1 min read
Lecture12: Projections & Subspaces
Projections Projection Matrix Subspaces

Lecture12: Projections & Subspaces

· 1 min read
Lecture13: QR Decomposition, Least Squares, Gram-Schmidt
LSQ Linear Regression QR Gram-Schmidt

Lecture13: QR Decomposition, Least Squares, Gram-Schmidt

· 1 min read
Lecture14: Determinants
Determinants Permutations Cramer’s Rule

Lecture14: Determinants

· 1 min read
Lecture15: Eigenvalues, Eigenvectors, PS/D Matrices
Eigenvalues Eigenvectors Decomposition PS/D

Lecture15: Eigenvalues, Eigenvectors, PS/D Matrices

· 1 min read

✌️ Explore Topics

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4-Subspaces 2 Posts
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Abstraction 1 Post
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Basis 2 Posts
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CR Decomposition 1 Post
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Column-Spaces 1 Post
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Columnspace 1 Post