Gradient methods

Gradient methods, often referred to as gradient descent algorithms, are optimization techniques used primarily in machine learning and mathematical optimization to find the minimum of a function. These methods are particularly useful for minimizing cost functions in various applications, such as training neural networks, linear regression, and logistic regression. ### Key Concepts: 1. **Gradient**: The gradient of a function is a vector that points in the direction of the steepest ascent of that function.