The Matrix Calculus You Need For Deep Learning
2025-03-29
This paper aims to explain all the matrix calculus you need to understand deep neural network training. Assuming only Calculus 1 knowledge, it progressively builds from scalar derivative rules to vector calculus, matrix calculus, Jacobians, and chain rules. Through derivations and examples, the authors demystify these concepts, making them accessible. The paper concludes with a summary of key matrix calculus rules and terminology.