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。
前向传播是神经网络通过层级结构和参数，将输入数据逐步转换为预测结果的过程，实现输入与输出之间的复杂映射。
In lots of instances, the consumer maintains the more mature version with the computer software since the more recent Model has steadiness concerns or can be incompatible with downstream purposes.
was the final Formal release of Python two. In an effort to continue being existing with stability patches and proceed savoring the entire new developments Python has to offer, corporations required to improve to Python three or commence freezing needs and decide to legacy lengthy-time period help.
On this situation, the user remains to be functioning an older upstream Variation of your application with backport packages used. This doesn't provide the complete safety features and advantages of functioning the most recent Model of your software program. People should really double-Test to check out the particular software program update quantity to be sure They're updating to the most up-to-date Variation.
反向传播的目标是计算损失函数相对于每个参数的偏导数，以便使用优化算法（如梯度下降）来更新参数。
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Backporting is often a catch-all term for virtually any action that applies updates or patches from a more moderen Edition of software package to an older version.
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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。
Perform strong testing to make certain that the backported code or backport offer maintains entire functionality in the IT architecture, in addition to addresses the fundamental stability flaw.
参数偏导数：在计算了输出层和隐藏层的偏导数之后，我们需要进一步计算损失函数相对于网络参数的偏导数，即权重和偏置的偏导数。
根据问题的类型，输出层可以直接输出这些值（回归问题），或者通过激活函数（如softmax）转换为概率分布（分类问题）。