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Understanding Gradient Descent Basics by pcjoshi02 is a document available to read on EtoBox.
Gradient descent is an iterative algorithm that finds the minimum of a function by taking steps proportional to the negative of the gradient of the function. It works by computing the gradient at a point and moving slightly in the opposite direction to reach the minimum. Limitations include only finding local minima, step size affecting convergence, and requiring differentiability of the function.
- Author
- pcjoshi02
- Language
- EN