的训练数据 - 翻译成英语

• training data
• training stats

在 中文 中使用 的训练数据 的示例及其翻译为 英语

如你所见，分类准确率在使用更多的训练数据时提升了很大。
As you can see, the classification accuracies improve considerably as we use more training data.

它确保网络对现有的训练数据不至于太“适合”，从而有助于缓解过拟合问题。
It makes sure that the network isn't getting too“fitted” to the training data and thus helps alleviate the overfitting problem.

特定组的训练数据输入的响应平均值被认为是该组的预测。
The mean of responses of the training data inputs of particular group is considered as prediction for that group.

其次，我们已经知道深度学习技术需要大量的训练数据，而对于某些垂直行业而言这可能是一种约束和限制。
Secondly, Deep Learning techniques have been known to require lots of training data which may act as a constraint for certain industry verticals.

其中一个挑战是人工智能目前需要大量的训练数据，而这些数据只能用于特定类型的问题。
One challenge is that AI currently needs large volumes of training data, and that is available only for particular types of problems.

难预测的训练数据被赋予更多的权重，而容易预测的数据被赋予较少的权重。
Training data that is hard to predict is given more more weight, whereas easy to predict instances are given less weight.

他们会逐渐意识到，准确预测不仅需要大量的训练数据，还需要特定的行为元数据。
They will increasingly realize that accurate predictions require not just a large volume of training data, but a particular type: behavioral metadata.

由于大多数的训练数据都很相似，网络在分辨不同的目标时遇到了困难。
Because most of the training data is quite similar, the network struggles to differentiate between different objects.

朴素贝叶斯只需要少量的训练数据来估计必要的参数。
An advantage of naive Bayes is that it only requires a small amount of training data to estimate the parameters necessary for classification.

默认情况下，10%的训练数据是按照这种方法提供的，但可以使用--silence_percentage控制该比例。
By default 10% of the training data is supplied like this, but the--silence_percentage can be used to control the proportion.

现在使用大量的训练数据和处理能力，可以教机器理解并和人类说话。
Using large amounts of training data and processing power, it's now possible to teach a machine to understand and speak to humans.

在机器学习中，根据所使用的训练数据的数量和类型，结果可能有偏差或不准确。
In machine learning, the results can be biased or inaccurate based on the volume and type of training data used.

简单说，所有的训练数据都留在用户的设备上，而且上传到云端的个别更新也不会存储到云端。
All the training data remains on a user's device, and no individual update is identifiably stored in the cloud.

Skip-gram：能够很好地处理少量的训练数据，而且能够很好地表示不常见的单词或短语.
Skip-gram: works well with small amount of the training data, represents well even rare words or phrases.

所有的训练数据仍然在每名终端用户的设备中，个人更新不会在云端保存。
Most importantly, all the training data remains on a user's device, and no individual update is identifiably stored in the cloud.

为了构建应用程序，你需要把每套房子的训练数据输入到你的机器学习算法中。
To build your app, you feed your training data about each house into your machine learning algorithm.

那么新的训练数据进入时，kNN执行两个基本步骤：.
When new unlabeled data comes in, kNN operates in 2 basic steps.

现在的机器学习技术通常依赖于大量的训练数据、巨大的计算资源、耗费时间的试验与误差方法论。
Current machine learning techniques generally rely on huge amounts of training data, vast computational resources, and a time-consuming trial and error methodology.

深度学习应用程序的训练数据通常决定其功能的范围和限度。
The training data of a deep learning application often determines the scope and limit of its functionality.

这很重要，因为在某些领域很难积累足够多的训练数据。
That's important, since it can be difficult to accumulate a sizable enough set of training data in some domains.