This repository implements the Gradient Descent algorithm for both minimization and maximization of functions. Gradient Descent is a widely-used optimization technique in machine learning, data science, and numerical optimization. It works by iteratively adjusting parameters to find the optimal solution, either by minimizing or maximizing the objective function. In this repository, I will explore various techniques and approaches to further enhance the application of Gradient Descent, including experimenting with different types and variants of the algorithm.