Linear Algebra Cheat Sheet for Machine Learning

Last Updated on August 9, 2019

All of the Linear Algebra Operations that You Need to Use
in NumPy for Machine Learning.

The Python numerical computation library called NumPy provides many linear algebra functions that may be useful as a machine learning practitioner.

In this tutorial, you will discover the key functions for working with vectors and matrices that you may find useful as a machine learning practitioner.

This is a cheat sheet and all examples are short and assume you are familiar with the operation being performed.

You may want to bookmark this page for future reference.

Kick-start your project with my new book Linear Algebra for Machine Learning, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

Linear Algebra Cheat Sheet for Machine Learning
Photo by Christoph Landers, some rights reserved.

Overview

This tutorial is divided into 7 parts; they are:

1. Arrays
2. Vectors
3. Matrices
4. Types of Matrices
5. Matrix Operations
6. Matrix Factorization
7. Statistics