10 Powerful Applications of Linear Algebra in Data Science (with Multiple Resources)
Overview
- Linear algebra powers various and diverse data science algorithms and applications
- Here, we present 10 such applications where linear algebra will help you become a better data scientist
- We have categorized these applications into various fields – Basic Machine Learning, Dimensionality Reduction, Natural Language Processing, and Computer Vision
Introduction
If Data Science was Batman, Linear Algebra would be Robin. This faithful sidekick is often ignored. But in reality, it powers major areas of Data Science including the hot fields of Natural Language Processing and Computer Vision.
I have personally seen a LOT of data science enthusiasts skip this subject because they find the math too difficult to understand. When the programming languages for data science offer a plethora of packages for working with data, people don’t bother much with linear algebra.
That’s a mistake. Linear algebra is behind all the powerful machine learning algorithms we are so familiar with. It is a vital cog in a data scientists’ skillset. As we will soon see, you should consider linear algebra as a