All Courses

Linear Algebra Fundamentals for Machine Learning

Chapter 1: Why Linear Algebra Matters in Machine Learning

Representing Data with Vectors and Matrices

Linear Algebra in Machine Learning Algorithms

Core Concepts Overview

Setting Up Your Python Environment

Quiz for Chapter 1

Chapter 2: Getting Started with NumPy for Numerical Computing

Introduction to NumPy Arrays

Creating NumPy Arrays

Array Indexing and Slicing

Basic Array Operations

Array Attributes and Shape Manipulation

Hands-on: NumPy Array Creation and Manipulation

Quiz for Chapter 2

Chapter 3: Working with Vectors

What is a Vector?

Vector Notation

Vectors in Python using NumPy

Vector Addition and Subtraction

Scalar Multiplication

Vector Norms: Measuring Length

The Dot Product

Hands-on: Vector Operations with NumPy

Quiz for Chapter 3

Chapter 4: Working with Matrices

What is a Matrix?

Matrix Notation and Dimensions

Matrices in Python using NumPy

Types of Matrices: Square, Identity, Zero

Diagonal and Triangular Matrices

Hands-on: Matrix Creation with NumPy

Quiz for Chapter 4

Chapter 5: Essential Matrix Operations

Matrix Addition and Subtraction

Scalar Multiplication

Matrix Transpose

Matrix Multiplication: The Dot Product

Properties of Matrix Multiplication

Hands-on: Matrix Operations with NumPy

Quiz for Chapter 5

Chapter 6: Systems of Linear Equations and Matrix Inverses

Representing Linear Equations with Matrices

The Concept of a Solution

The Identity Matrix Revisited

The Matrix Inverse

Conditions for Invertibility

Solving Ax = b using the Inverse

Calculating Inverses with NumPy

Solving Linear Systems with NumPy

Hands-on: Solving Systems with NumPy

Quiz for Chapter 6

This course has been archived: A newer version with updated syllabus and improved content is now available.

All Courses

Linear Algebra Fundamentals for Machine Learning

Chapter 1: Why Linear Algebra Matters in Machine Learning

Representing Data with Vectors and Matrices

Linear Algebra in Machine Learning Algorithms

Core Concepts Overview

Setting Up Your Python Environment

Quiz for Chapter 1

Chapter 2: Getting Started with NumPy for Numerical Computing

Introduction to NumPy Arrays

Creating NumPy Arrays

Array Indexing and Slicing

Basic Array Operations

Array Attributes and Shape Manipulation

Hands-on: NumPy Array Creation and Manipulation

Quiz for Chapter 2

Chapter 3: Working with Vectors

What is a Vector?

Vector Notation

Vectors in Python using NumPy

Vector Addition and Subtraction

Scalar Multiplication

Vector Norms: Measuring Length

The Dot Product

Hands-on: Vector Operations with NumPy

Quiz for Chapter 3

Chapter 4: Working with Matrices

What is a Matrix?

Matrix Notation and Dimensions

Matrices in Python using NumPy

Types of Matrices: Square, Identity, Zero

Diagonal and Triangular Matrices

Hands-on: Matrix Creation with NumPy

Quiz for Chapter 4

Chapter 5: Essential Matrix Operations

Matrix Addition and Subtraction

Scalar Multiplication

Matrix Transpose

Matrix Multiplication: The Dot Product

Properties of Matrix Multiplication

Hands-on: Matrix Operations with NumPy

Quiz for Chapter 5

Chapter 6: Systems of Linear Equations and Matrix Inverses

Representing Linear Equations with Matrices

The Concept of a Solution

The Identity Matrix Revisited

The Matrix Inverse

Conditions for Invertibility

Solving Ax = b using the Inverse

Calculating Inverses with NumPy

Solving Linear Systems with NumPy

Hands-on: Solving Systems with NumPy

Quiz for Chapter 6

This course has been archived: A newer version with updated syllabus and improved content is now available.