English(EN) What Is Gradient Descent and How Does It Work?

梯度下降详解：优化神经网络

作者 PulseAugur 编辑部 · [2 个来源] · 2026-09-30 05:51

梯度下降是一种迭代优化算法，用于机器学习中最小化一个函数，通常是神经网络中的损失函数。它通过计算损失函数相对于网络权重的梯度（或斜率）来工作。然后，算法沿着梯度的相反方向进行迭代，以找到损失较低的点。学习率是一个关键的超参数，它决定了这些步长的大小，从而决定了模型收敛到最小值的速度。 AI

影响解释了一种对训练机器学习模型至关重要的基本优化技术。

排序理由该集群解释了一种核心的机器学习算法——梯度下降，这是基础研究。

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Towards AI TIER_1 Français(FR) · Sanika Tare · 2026-10-01 13:01

梯度下降详解

<h4><em>Backprop told the network what went wrong. Now it has to actually fix it.</em></h4><p>At the end of the last article, backpropagation had done its job. Every weight in the network had a gradient attached, a little note saying which way it should move. But a note doesn’t c…
Medium — Claude tag TIER_1 English(EN) · Narayanamrajsekhar · 2026-09-30 05:51

什么是梯度下降及其工作原理？

<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@narayanamrajsekhar/what-is-gradient-descent-and-how-does-it-work-a3b28665205b?source=rss------claude-5"><img src="https://cdn-images-1.medium.com/max/1536/1*K6WcCCpwMW0S_ZziQB_dfg.png" width="…