What is the translation of " 无监督机器学习 " in English?

• unsupervised machine learning
• unsupervised ML
• unsupervised machine-learning

Examples of using 无监督机器学习 in Chinese and their translations into English

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

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

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。
Unsupervised machine learning is particularly useful for the type of big data analytics that interests many enterprise leaders.

此外，无监督机器学习模型可以不间断地分析和处理新数据，然后自动更新自身模型以反映最新趋势。
Also, unsupervised ML models can continuously analyze and process new data and then autonomously update its models to reflect the latest trends.

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。
Whereas in unsupervised machine learning, the model learns by discovering information by itself.

本课程描述了神经网络在机器学习中的应用:深度学习、递归网络、强化学习以及其他有监督和无监督机器学习算法。
It describes the use of neural networks in machine learning: deep learning, recurrent networks, and other supervised and unsupervised machine-learning algorithms.

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。
Today, the machine learning features of X-Pack are focused on providing“Time Series Anomaly Detection” capabilities using unsupervised machine learning.

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。
Unsupervised machine learning depends on recognizing patterns contained within data and comparing them to other data or search queries.

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

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。
Probability and Statistics may not be as flashy as Deep Learning or Unsupervised Machine Learning, but they are the bedrock of Data Science.

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。
Various techniques, such as supervised/ unsupervised machine learning and neural networks, should be employed to analyze data and provide actionable insight.

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。
By using unsupervised machine learning, our AI-powered solution ingests, analyzes, and visualizes omni-channel customer feedback in near-real time.

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。
It can also be used to develop generative adversarial networks(GANs), a class of AI algorithms found in 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。
GANs(generative adverserial networks) are a type of AI used to carry out unsupervised machine learning.

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。
Scikit-learn is a free and open source software that helps you tackle supervised and unsupervised machine learning problems.

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)。
However we can also leave the computer program to do all the relevant learning by itself(unsupervised machine learning).

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.
Supervised and unsupervised machine learning tools for data, images and sounds including artificial neural networks.

而在不久的将来，无监督机器学习还将会有一个大的飞跃。
In addition, there will be a big leap in unsupervised machine learning in the near future.

无监督机器学习最常用于将数据分成几组类似的样本。
The most common use of unsupervised machine learning is to cluster data into groups of similar examples.

无监督机器学习的一个示例是Facebook的预测式面部识别算法，它可以在照片中识别人。
An example of unsupervised machine learning is Facebook's predictive facial recognition algorithm, that identifies people in photographs.

现在，天文学家正利用无监督机器学习来自动完成以前需要由数千名志愿者才能完成的任务。
Astronomers are now leveraging the power of unsupervised Machine Learning to automate this task, which was previously done by thousands of volunteers.

在未来几年，我们可能会看到无监督机器学习算法的改进。
In the coming years, we are likely to see improvements in unsupervised machine learning algorithms.

通过整体数据分析实践，运用先进的AI和无监督机器学习技术等，我们可以在保持用户隐私的同时获得高水平的智能分析能力。
Through holistic data analysis practices and advanced AI and unsupervised machine learning, we can gain a high level of intelligence while preserving user privacy.

无监督机器学习：K-means聚类.
Unsupervised learning: K-means clustering.

无监督机器学习被用来对抗没有历史标签的数据。
Unsupervised learning is used against data that has no historical labels.

有两种类型的无监督机器学习问题：聚类和关联。
There are two types of unsupervised learning problems- clustering and association.

它概要介绍了监督机器学习、无监督机器学习和强化机器学习的相关知识，并详细介绍有关Spark和自然语言处理(NLP)的相关信息。
It gives an overview of supervised learning, unsupervised learning, and reinforcement learning methods as well as detailed information about Spark and natural language processing(NLP).