AIOfferly刷题记录

题目

What is gradient descent, can you explain it in simple terms?

答案

Gradient Descent is an optimization algorithm used to minimize the error of a machine learning model. It first computes the gradient, which indicates how much the loss function changes with respect to the model parameters. By updating the parameters in the direction of the negative gradient, it reduces the loss. The size of each step taken during this process is controlled by a parameter called the learning rate. The goal of gradient descent is to keep updating the parameters until the loss function reaches its lowest possible value, meaning the model is as accurate as possible.

梯度下降是一种优化算法，用于最小化机器学习模型的误差。它首先计算梯度，表示损失函数相对于模型参数的变化程度。通过沿负梯度方向更新参数，可以减少损失。在这个过程中，每次更新的步长由一个称为学习率的参数控制。梯度下降的目标是不断更新参数，直到损失函数达到其可能的最低值，也就是说，模型的准确性达到了最佳状态。