What are Eigenvalues and Eigenvectors?

A must-know concept for Machine Learning

Eigenvectors and eigenvalues live in the heart of the data science field. This article will aim to explain what eigenvectors and eigenvalues are, how they are calculated and how we can use them. It’s a must-know topic for anyone who wants to understand machine learning in-depth.

Eigenvalues and eigenvectors form the basics of computing and mathematics. They are heavily used by scientists.

Article Structure

This article is structured in six parts:

1. I will start by providing a brief introduction of eigenvectors and eigenvalues.
2. Then I will illustrate their use-cases and applications.
3. I will then explain the building blocks that make up the eigenvalues and eigenvectors such as the basics of matrix addition and multiplication so that we can refresh our knowledge and understand the concepts thoroughly.
4. I will then illustrate how eigenvectors and eigenvalues are calculated.
5. Subsequently, a working example of how eigenvectors and eigenvalues are calculated will be presented.
6. Finally, I will outline how we can compute the eigenvectors and eigenvalues in Python.

1. Eigenvectors and Eigenvalues Introduction