链式法则不仅适用于简单的两层神经网络，还可以扩展到具有任意多层结构的深度神经网络。这使得我们能够训练和优化更加复杂的模型。
算法从输出层开始，根据损失函数计算输出层的误差，然后将误差信息反向传播到隐藏层，逐层计算每个神经元的误差梯度。
在神经网络中，损失函数通常是一个复合函数，由多个层的输出和激活函数组合而成。链式法则允许我们将这个复杂的复合函数的梯度计算分解为一系列简单的局部梯度计算，从而简化了梯度计算的过程。
Backporting is often a multi-stage process. In this article we outline The essential ways to produce and deploy a backport:
was the final Formal launch of Python 2. So as to keep on being existing with security patches and proceed making the most of all of the new developments Python has to offer, companies required to up grade to Python three or get started freezing prerequisites and decide to legacy lengthy-term aid.
偏导数是多元函数中对单一变量求导的结果，它在神经网络反向传播中用于量化损失函数随参数变化的敏感度，从而指导参数优化。
Establish what patches, updates or modifications are offered to address this problem in later variations of exactly the same computer software.
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偏导数是指在多元函数中，对其中一个变量求导，而将其余变量视为常数的导数。
根据计算得到的梯度信息，使用梯度下降或其他优化算法来更新网络中的权重和偏置参数，以最小化损失函数。
一章中的网络是能够学习的，但我们只将线性网络用于线性可分的类。 当然，我们想写通用的人工
These concerns have an impact on not only the primary application but also all dependent libraries and forked applications to general public repositories. It is important to think about how Each and every backport fits throughout the Corporation’s General security strategy, together with the IT architecture. This is applicable to equally upstream software program purposes along with the kernel alone.