网络的权重和偏置如下（这些值是随机初始化的，实际情况中会使用随机初始化）：
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 usually a multi-step system. Listed here we define the basic steps to develop and deploy a backport:
Backporting is a standard procedure to handle a acknowledged bug within the IT surroundings. At the same time, counting on a legacy codebase introduces other probably sizeable security implications for companies. Relying on previous or legacy code could lead to introducing weaknesses or vulnerabilities within your natural environment.
Equally as an upstream software program application affects all downstream applications, so far too does a backport placed on the core application. This is certainly also accurate If your backport is utilized inside the kernel.
反向传播算法基于微积分中的链式法则，通过逐层计算梯度来求解神经网络中参数的偏导数。
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的原理及实现过程进行说明，通俗易懂，适合新手学习，附源码及实验数据集。
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Backports is often a successful way to handle stability flaws and vulnerabilities in older variations of software. Nevertheless, each backport introduces a fair volume of complexity within the procedure architecture and will be high-priced to keep up.
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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 difficulties affect not just the leading software but will also all dependent libraries and forked purposes to public repositories. It can be crucial to take into account how Each and every backport suits within the Business’s General security technique, plus the IT architecture. This applies to both of those upstream computer software applications and the kernel itself.