Matrix Calculus for Machine Learning and Beyond! — a free ebook from MIT.

This is the 2025 MIT textbook by Alan Edelman, Steven G. Johnson, and Paige Bright.

The book directly connects matrix calculus to modern machine learning.

Inside:

*   Derivatives of matrices and vectors
*   Jacobian and Hessian
*   Matrix decompositions
*   Optimization
*   Differentiation in reverse mode
*   Backpropagation of error
*   Automatic differentiation
*   Derivatives through ODEs
*   Problems focused on machine learning

This is a comprehensive mathematical bridge between linear algebra, calculus, optimization, backpropagation, and machine learning.

Free ebook:
https://geni.us/Matrix-Calculus-Book

@Machine_learn