The Role of Linear Algebra in Developing Machine Learning Solutions

The branch of mathematics known as “linear algebra” deals with vectors, matrices, and linear transformations. It is useful in a variety of disciplines, including computer science, physics, engineering, and machine learning, where it is essential to data analysis, classification, and machine learning algorithms. Additionally, machine learning is used to allow computer programmers to determine, without explicit programming, which of its applications—graphing, regression, and predicating is most closely related to mathematics, primarily linear algebra. Because machine learning is strongly related to statistics, we will briefly explain some statistical ideas before examining what linear algebra and machine learning are in this work. Afterwards, we demonstrate how linear algebra is used in support vector machines and linear regression, two types of machine learning algorithms.