UNSUPERVISED MACHINE LEARNING 中文是什么意思 - 中文翻译

• 无监督机器学习
• 无人监督的机器学习
• 非监督式机器学习

在 英语 中使用 Unsupervised machine learning 的示例及其翻译为 中文

Python unsupervised machine learning.
Python无监督学习机器学习.

This has to do with the difference between supervised and unsupervised machine learning.
这恰恰是有监督和无监督机器学习之间的区别。

Supervised and unsupervised machine learning techniques.
监督和非监督机器学习技术。

Differentiate between Supervised Machine Learning and Unsupervised Machine learning?
有监督机器学习和无监督机器学习的区别?

In contrast, unsupervised machine learning does not involve training.
相反，无监督的机器学习不涉及训练。

Here are some guidelines on choosing between supervised and unsupervised machine learning:.
下面是选择监督式或者无监督机器学习的一些准则：.

In unsupervised machine learning, the examples don't contain labels.
而在非监督式机器学习中，样本不包含标签。

Home Trends Facebook is using unsupervised machine learning for translations.
Facebook正在使用无人监督的机器学习进行翻译.

GANs(generative adverserial networks) are a type of AI used to carry out unsupervised machine learning.
GAN（生成性对抗网络）是一种用于执行无监督机器学习的AI。

Facebook is using unsupervised machine learning for translations.
Facebook正在使用无人监督的机器学习进行翻译.

However we can also leave the computer program to do all the relevant learning by itself(unsupervised machine learning).
但是，我们也可以让计算机程序自己完成所有相关的学习(无监督机器学习)。

Previous articleFacebook is using unsupervised machine learning for translations.
Facebook正在使用无人监督的机器学习进行翻译.

Whereas in unsupervised machine learning, the model learns by discovering information by itself.
而在无监督机器学习中，模型是通过自身发现信息来学习的。

Scikit-learn is a free and open source software that helps you tackle supervised and unsupervised machine learning problems.
Scikit-learn是一款免费的开源软件，可以帮助你解决监督和无监督机器学习问题。

Another example of unsupervised machine learning is principal component analysis(PCA).
非监督式机器学习的另一个例子是主成分分析(PCA)。

It can also be used to develop generative adversarial networks(GANs), a class of AI algorithms found in unsupervised machine learning.
它还可用于开发生成对抗网络（GAN），这是一种在无监督机器学习中发现的AI算法类别。

Learning about supervised and unsupervised machine learning is no small feat.
学习监督式和非监督式机器学习是不小的壮举。

Unsupervised machine learning is particularly useful for the type of big data analytics that interests many enterprise leaders.
无监督机器学习对于许多企业领导者感兴趣的大数据分析类型特别有用。

Probability and Statistics may not be as flashy as Deep Learning or Unsupervised Machine Learning, but they are the bedrock of Data Science.
概率和统计可能不像深度学习或无监督机器学习那么浮华，但它们是数据科学的基石，更是机器学习的基石。

Instead, they use unsupervised machine learning and compare random texts in different languages.
相反，他们使用未监督的机器学习，并比较不同语言的随机文本。

Today, the machine learning features of X-Pack are focused on providing“Time Series Anomaly Detection” capabilities using unsupervised machine learning.
今天发布的X-Pack机器学习特性，旨在通过无监督机器学习提供“时间序列数据异常检测”的能力。

Another example of unsupervised machine learning is principal component analysis(PCA).
无监督机器学习的另一个例子是主成分分析（principalcomponentanalysis，PCA）。

As only having a supervised approach comes with significant limitations, deep reinforcement learning will play a key role in making unsupervised machine learning more efficient.
由于监督式学习方法饱受限制，深度强化式学习将成为主流，使得无监督式机器学习更有效率。

Supervised and unsupervised machine learning tools for data, images and sounds including artificial neural networks.
为包括神经网络在内的数据、图像和声音的有监督和无监督机器学习提供工具.

Unsupervised machine learning depends on recognizing patterns contained within data and comparing them to other data or search queries.
无监督机器学习取决于识别数据中包含的模式并将其与其他数据或搜索查询进行比较。

One of the few successful techniques in unsupervised machine learning, and are quickly revolutionizing our ability to perform generative tasks.
它们是无监督机器学习中少数成功的技术，并且这种技术正在快速革新我们执行生成任务的能力。

Unsupervised machine learning can be quite powerful in its own right, and clustering is definitely the most usual expression of this group of issues.
无监督的机器学习本身就非常强大，而聚类是迄今为止这类问题中最常见的方式。

Various techniques, such as supervised/ unsupervised machine learning and neural networks, should be employed to analyze data and provide actionable insight.
应该采用各种技术，如监督/无监督机器学习和神经网络，进行数据分析并提供具体行动方案。

By using unsupervised machine learning, our AI-powered solution ingests, analyzes, and visualizes omni-channel customer feedback in near-real time.
通过使用无监督机器学习，我们的人工智能解决方案抓取，分析，并几乎实时的可视化全渠道客户反馈。

IAGON uses both supervised and unsupervised machine learning method known as semi-supervised learning to both process and distribute data across decentralized networks.
IAGON使用既有监督的也有无监督机器学习方法（被称为半监督式学习），通过去中心化的网络处理和分配数据。