Taylor Series to Constrained Optimization to Linear Least Squares From: https://medium.com/swlh/gradient-based-optimizations-jacobians-jababians-hessians-b7cbe62d662d Jacobian Sometimes we need to find all of the partial derivatives of a function whose input and output are both vectors. The matrix containing all such partial derivatives is the Jacobian. Given: The Jacobian matrix J is given by: Example of Jacobian Matrix Let’s say: The … Continue reading Gradient Based Optimizations: Jacobians, Jababians & Hessians →