Linear algebra is a fundamental branch of mathematics that is highly relevant to deep learning. Deep neural networks extensively utilize matrix operations, which are a key component of linear algebra. Matrix multiplication, transpose, and inversion, for instance, enable the transformation of data within networks. Additionally, linear algebra concepts like eigenvalues and eigenvectors assist in understanding the behavior of neural networks and optimizing their performance.