AI class prerequisites: Difference between revisions
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== Basic Probability == | == Basic Probability == | ||
<youtube>uzkc-qNVoOk</youtube> | |||
== Probability (Part 6) - Conditional Probability == | == Probability (Part 6) - Conditional Probability == | ||
<youtube>xf3vfczoCho</youtube> | |||
== Probability (Part 7) - Bayes' Rule == | == Probability (Part 7) - Bayes' Rule == | ||
<youtube>BLcgeLALLnc</youtube> | |||
== Probability (Part 8) - More Bayes' Rule == | == Probability (Part 8) - More Bayes' Rule == | ||
<youtube>VVr8snbaxZg</youtube> | |||
== Introduction to Random Variables == | == Introduction to Random Variables == | ||
<youtube>IYdiKeQ9xEI</youtube> | |||
== Probability Density Functions == | == Probability Density Functions == | ||
<youtube>Fvi9A_tEmXQ</youtube> | |||
== Expected Value: E(X) == | == Expected Value: E(X) == | ||
<youtube>j__Kredt7vY</youtube> | |||
= Linear Algebra Prerequisites = | = Linear Algebra Prerequisites = | ||
== Introduction to Matrices == | == Introduction to Matrices == | ||
<youtube>xyAuNHPsq-g</youtube> | |||
== Matrix Multiplication (Part 1) == | == Matrix Multiplication (Part 1) == | ||
<youtube>aKhhYguY0DQ</youtube> | |||
== Matrix Multiplication (Part 2) == | == Matrix Multiplication (Part 2) == | ||
<youtube>OAh573i_qn8</youtube> | |||
== Inverse Matrix (Part 1) == | == Inverse Matrix (Part 1) == | ||
<youtube>iUQR0enP7RQ</youtube> | |||
== Inverting Matrices (Part 2) == | == Inverting Matrices (Part 2) == | ||
<youtube>S4n-tQZnU6o</youtube> | |||
== Inverting Matrices (Part 3) == | == Inverting Matrices (Part 3) == | ||
<youtube>obts_JDS6_Q</youtube> | |||
== Matrices to Solve a System of Equations == | == Matrices to Solve a System of Equations == | ||
<youtube>AUqeb9Z3y3k</youtube> | |||
== Singular Matrices == | == Singular Matrices == | ||
<youtube>UqyN7-tRS00</youtube> | |||
== Introduction to Vectors == | == Introduction to Vectors == | ||
<youtube>5cWB52I-SF0</youtube> | |||
== Vector Dot Product and Vector Length == | == Vector Dot Product and Vector Length == | ||
<youtube>WNuIhXo39_k</youtube> | |||
== Defining the Angle Between Vectors == | == Defining the Angle Between Vectors == | ||
<youtube>5AWob_z74Ks</youtube> | |||
== Cross Product Introduction == | == Cross Product Introduction == | ||
<youtube>pJzmiywagfY</youtube> | |||
== Matrix Vector Products == | == Matrix Vector Products == | ||
<youtube>7Mo4S2wyMg4</youtube> | |||
== Linear Transformations as Matrix Vector Products == | == Linear Transformations as Matrix Vector Products == | ||
<youtube>PErhLkQcpZ8</youtube> | |||
== Linear Transformation Examples: Scaling and Reflections == | == Linear Transformation Examples: Scaling and Reflections == | ||
<youtube>qkfODKmZ-x4</youtube> | |||
== Linear Transformation Examples: Rotations in R2 == | == Linear Transformation Examples: Rotations in R2 == | ||
<youtube>lPWfIq5DzqI</youtube> | |||
== Introduction to Projections == | == Introduction to Projections == | ||
<youtube>27vT-NWuw0M</youtube> | |||
== Exploring the Solution Set of Ax = b == | == Exploring the Solution Set of Ax = b == | ||
<youtube>1PsNIzUJPkc</youtube> | |||
== Transpose of a Matrix == | == Transpose of a Matrix == | ||
<youtube>2t0003_sxtU</youtube> | |||
== 3x3 Determinant == | == 3x3 Determinant == | ||
<youtube>0c7dt2SQfLw</youtube> | |||
== Introduction to Eigenvalues and Eigenvectors == | == Introduction to Eigenvalues and Eigenvectors == | ||
<youtube>PhfbEr2btGQ</youtube> | |||
Latest revision as of 15:01, 28 August 2017
Here we document the prerequisite learning for the AI class.
Resources
Probability Prerequisites
- Basic Probability
- Probability (Part 6) - Conditional Probability
- Probability (Part 7) - Bayes' Rule
- Probability (Part 8) - More Bayes' Rule
- Introduction to Random Variables
- Probability Density Functions
- Expected Value: E(X)
Linear Algebra Prerequisites
- Introduction to Matrices
- Matrix Multiplication (Part 1)
- Matrix Multiplication (Part 2)
- Inverse Matrix (Part 1)
- Inverting Matrices (Part 2)
- Inverting Matrices (Part 3)
- Matrices to Solve a System of Equations
- Singular Matrices
- Introduction to Vectors
- Vector Dot Product and Vector Length
- Defining the Angle Between Vectors
- Cross Product Introduction
- Matrix Vector Products
- Linear Transformations as Matrix Vector Products
- Linear Transformation Examples: Scaling and Reflections
- Linear Transformation Examples: Rotations in R2
- Introduction to Projections
- Exploring the Solution Set of Ax = b
- Transpose of a Matrix
- 3x3 Determinant
- Introduction to Eigenvalues and Eigenvectors
Probability Prerequisites
Basic Probability
Probability (Part 6) - Conditional Probability
Probability (Part 7) - Bayes' Rule
Probability (Part 8) - More Bayes' Rule
Introduction to Random Variables
Probability Density Functions
Expected Value: E(X)
Linear Algebra Prerequisites
Introduction to Matrices
Matrix Multiplication (Part 1)
Matrix Multiplication (Part 2)
Inverse Matrix (Part 1)
Inverting Matrices (Part 2)
Inverting Matrices (Part 3)
Matrices to Solve a System of Equations
Singular Matrices
Introduction to Vectors
Vector Dot Product and Vector Length
Defining the Angle Between Vectors
Cross Product Introduction
Matrix Vector Products
Linear Transformations as Matrix Vector Products
Linear Transformation Examples: Scaling and Reflections
Linear Transformation Examples: Rotations in R2
Introduction to Projections
Exploring the Solution Set of Ax = b
Transpose of a Matrix
3x3 Determinant
Introduction to Eigenvalues and Eigenvectors