What is the translation of " LABELED DATA " in Chinese?

• 标记数据
• 标签数据
• 标注的数据

Examples of using Labeled data in English and their translations into Chinese

The dearth of labeled data;
标签数据的缺乏；.

If you have labeled data, it's a supervised learning problem.
如果你有数据标签，这是一个监督学习问题。

And then of course, you need labeled data.
当然，你需要标记数据。

Generating this labeled data is expensive.
收集有标签的数据是一件昂贵的工作。

Supervised machine learning requires labeled data.
监督式机器学习需要标记数据.

DNNs rely on large sets of labeled data to perform their functions.
DNN依赖于大量的标记数据来执行其功能。

This approach uses large amounts of labeled data.
这种方法需要使用大量的标记数据。

Labeled data as the few example problems that the teacher served in class.
并将数据标记作为教师在课堂上运用的少数示例。

It requires training labeled data.
因此需要有标注的训练数据。

Services for generating labeled data sets are increasingly using AI technologies.
用于生成标记数据集的服务越来越多地使用AI技术。

Today, deep learning is driven by carefully labeled data.
当下，深度学习由精心标注的数据驱动。

Categorize by input: If we have labeled data, it's a supervised learning problem.
通过输入分类：如果我们有标签数据，这是一个监督学习问题。

Today, deep learning is driven by carefully labeled data.
今天，深度学习是由认真标注的数据驱动的。

Categorize by input: If we have labeled data, it's a supervised learning problem.
由输入数据分类：当我们有标签数据，这属于有监督学习问题。

By doing so, you are training the machine by using labeled data.
通过这样做，您将使用标记数据训练机器。

Categorize by the input: If it is a labeled data, it's a supervised learning problem.
由输入数据分类：当我们有标签数据，这属于有监督学习问题。

LeCun of Facebook believes that researchers won't be forced to subsist on labeled data forever.
Facebook的LeCun相信，研究者不会永远依靠标记数据。

Categorize by the input: If it is a labeled data, it's a supervised learning problem.
通过输入分类：如果我们有标签数据，这是一个监督学习问题。

Even more notable is the fact that it can be trained via simulation, which eliminates the need for labeled data entirely.
且它的另一个优点是可以通过模拟来训练它，这完全消除了对标记数据的需求。

There are databases that offer labeled data, including ImageNet, which is a database with over 14 million images.
有些数据库提供标记数据，包括ImageNet，这是一个拥有1400多万张图像的数据库。

But like many others researchers, OpenAI aims to create neural nets that can learn without carefully labeled data.
但就像许多其他研究人员设想的，OpenAI旨在创建无须精心标注的数据就能学习的神经网络。

The problem:- a large amount of labeled data is needed- some of the current mission data labels are very limited.
存在的问题：-需要大量的标记数据-目前的某些任务数据标签很有限.

They are large, extremely complex neural networks that use small amounts of labeled data and much larger amounts of unlabeled data..
它们是大、且极其复杂的神经网络，使用少量的标记数据和更多的未标记数据。

If a few thousand dollars of labeled data is enough to fully automate the system, the data doesn't offer a competitive advantage.
如果支付几千美元的标记数据费用，就可以实现系统的全自动化，那么数据就不会创造出任何竞争优势。

And there will be new service-based companies that will outsource labeling to low-cost countries, as well as create labeled data through synthetic means.
那些新的服务型公司也将会把标记业务外包给低成本国家，同时通过合成手段来创建标签数据。

The company's platform assists companies in managing labeled data, enable rapid deployment of artificial intelligence applications.
该公司的平台可帮助公司管理标签数据，实现人工智能应用的快速部署。

Because unsupervised algorithms do not require labeled data, they could potentially exploit the tremendous amount of raw(unlabeled) sensory data we receive.
由于无监督算法不需要标记数据，因此它们可能会利用我们收到的大量原始未标记的感知数据。

Using deep learning, we are able to understand text better across multiple languages and use labeled data much more efficiently than traditional NLP techniques.
使用深度学习，我们可以更好地了解多种语言文本，在使用标签数据方面，也比传统自然语言理解技术高效地多。

After being shown large amounts of labeled data, the neural network can label new data based on what it has seen.
在获得大量的标记数据后，神经网络能够根据它看到的东西标记新的数据。

Transfer learning, where models previously trained for a problem with copious available labeled data are tailored for a new problem with limited labeled data.
转移学习，其中先前针对具有丰富可用标记数据的问题进行训练的模型针对具有有限标记数据的新问题而定制。