Matrices in Machine Learning

In machine learning, matrices are like organized grids of numbers that efficiently store and manipulate data. Think of a matrix as a table where each row might represent an individual data point (like a person's features: age, height, weight), and each column represents a specific feature. Matrices enable algorithms to perform complex calculations, such as transforming data, computing similarities, or adjusting model parameters, all in a structured way. They are essential for handling large datasets efficiently and for enabling the mathematical operations behind training and making predictions in machine learning models.