Gradient descent is used in the backpropagation (Backward Propagation of Errors) algorithm for supervised artificial neural network learning.Backpropagation is a process of analyzing errors, comparing them to the anticipated response, and re-running the model until it produces the desired outcome. According to experts, an algorithm called backpropagation is used in machine learning and artificial intelligence to train artificial neural networks by correcting errors. In a neural network, backpropagation reduces errors and enhances results, leading to more dependable machine responses. Errors are analyzed, compared to the expected response, and then the model is run again until the desired result is obtained. The steps (illustrated below) reflect how the human brain learns by making mistakes.
