How is linear algebra used in machine learning?

How is linear algebra used in machine learning?

Linear algebra is fundamental in machine learning for data representation, transformations, and optimization.

Can you give me an example of how matrices are used?

Sure! In machine learning, matrices are used to represent datasets, where each row is a data point and each column is a feature.

What about vector operations? How do they fit in?

Vector operations are crucial for calculations like dot products, which help in measuring similarity between data points.

Are there specific algorithms that rely heavily on linear algebra?

Yes, algorithms like Principal Component Analysis (PCA) and Support Vector Machines (SVM) heavily utilize linear algebra concepts.