What is the translation of " MACHINE LEARNING FRAMEWORKS " in Chinese?

• 机器学习框架

Examples of using Machine learning frameworks in English and their translations into Chinese

AI and Machine Learning Frameworks.
AI和机器学习框架.

Scikit-learn and Spark MLlib are machine learning frameworks.
Scikit-learning和SparkMLlib是机器学习框架。

Machine learning frameworks take advantage of the idea of abstraction to accomplish tasks.
机器学习构架则充分利用抽象概念来完成任务。

Supports all major machine learning frameworks.
支持所有主流机器学习框架.

Some machine learning frameworks have support for online augmentation, which can be accelerated on the GPU.
一些机器学习框架支持在线增强，可以再gpu上加速。

TensorFlow* is one of the leading deep learning and machine learning frameworks today.
TensorFlow*是一款领先的深度学习和机器学习框架。

Some are building machine learning frameworks to help organisations apply AI across use cases.
有些人正在构建机器学习框架，以帮助不同案例的AI应用。

InfoQ: How does R language compare with other Machine Learning frameworks like Spark MLlib?
InfoQ：如何去比较R语言和其它的机器学习框架，如SparkMLlib呢？?

Some are building machine learning frameworks to help organisations apply AI across use cases.
有些人正在构建机器学习框架，以帮助组织跨用例应用AI。

Generating user-friendly native code and linking open source machine learning frameworks like TensorFlow& Caffe.
生成用户友好的原代码，并将TensorFlow&Caffe等开源机器学习框架链接起来。

The best thing about machine learning frameworks is they come with pre-built components that help clients understand and code models easily.
关于机器学习框架的最实用之处是它们带有预构建的组件，可以帮助用户轻松地理解和编码模型。

Apache Mahout, being an open source framework, aims at the development of scalable machine learning frameworks.
ApacheMahout是一个开源框架，旨在开发可扩展的机器学习框架。

They can also use pre-built machine learning frameworks to accelerate the process;
他们还可以使用预先构建的机器学习框架来加速过程;

In this project, we built our tutorials using many different well-known Machine Learning frameworks such as Scikit-learn.
在这个项目中，我们使用许多不同的众所周知的机器学习框架（如scikit-learn）构建了我们的教程。

It also supports several machine learning frameworks, including TensorFlow, Caffe2 and ONNX.
此外，它还支持多种机器学习框架，包括TensorFlow、Caffe2和ONNX。

The comprehensive PowerVR NX Mapping Tool enables easy porting from industry standard machine learning frameworks such as Caffe and Tensorflow.
完整的PowerVRNXMappingTool能从业界标准的机器学习框架，包括Caffe和Tensorflow，轻松进行转换。

It also supports several machine learning frameworks, including TensorFlow, Caffe2 and ONNX.
更重要的是，它支持多种机器学习框架，包括TensorFlow、Caffe2和ONNX。

In part driven by deep learning, we see Increasingly more Spark users want to integrate Spark with distributed machine learning frameworks built for state-of-the-art training.
在深度学习的推动下，越来越多的Spark用户希望能够将Spark与为最先进的训练而构建的分布式机器学习框架集成起来。

There is a wide range of open source machine learning frameworks available in the market, which enable machine learning engineers to:.
现在有大量的开源机器学习框架，使机器学习工程师能够：.

Although the Python programming language powers most of the machine learning frameworks, JavaScript hasn't been left behind.
虽然Python是绝大多数的机器学习框架所采用的语言，但是JavaScript也并没有被抛下。

The open-source machine learning frameworks mentioned above can help anyone build machine learning models efficiently and easily.
上面提到的开源机器学习框架可以帮助大家高效、轻松地构建机器学习模型。

They can also use pre-built machine learning frameworks to accelerate the process.
他们也可以使用预先构建的机器学习框架来加速这个过程。

With an ever-growing collection of AI and machine learning frameworks, your applications should consider both edge computing and tight integration with sophisticated back-end cloud platforms.
随着人工智能和机器学习框架的不断增多，您的应用程序应该考虑边缘计算和与复杂的后端云平台的紧密集成。

What's more, it supports multiple machine learning frameworks, including TensorFlow, Caffe2 and ONNX.
此外，它还支持多种机器学习框架，包括TensorFlow、Caffe2和ONNX。

What's more, it supports multiple machine learning frameworks, including TensorFlow, Caffe2 and ONNX.
更重要的是，它支持多种机器学习框架，包括TensorFlow、Caffe2和ONNX。

What's more, it supports multiple machine learning frameworks, including TensorFlow, Caffe2 and ONNX.
更重要的是，它可支持多种机器学习框架，包括TensorFlow、Caffe2和ONNX。

It provides support for many common machine learning frameworks such as Caffe, MxNet and Tensorflow as well as Python and RESTful APIs.
它支持许多常见的机器学习框架，如Caffe、MxNet和Tensorflow，以及Python和RESTfulAPI等。

In addition, it works with open source machine learning frameworks such as PyTorch and TensorFlow to increase application flexibility.
除此之外，它还能够与开源机器学习框架配合使用（如PyTorch和TensorFlow），以提高应用的灵活性。

Importantly, it plays nicely with popular machine learning frameworks like Google's TensorFlow and Facebook's PyTorch, plus Arm's own solutions.
重要的是，它可以与流行的机器学习框架(如Google的TensorFlow和Facebook的PyTorch)以及Arm自己的解决方案很好地配合使用。

Since deep learning regained prominence in 2012, many machine learning frameworks have clamored to become the new favorite among researchers and industry practitioners.
自2012年深度学习再度成为焦点以来，很多机器学习框架成为研究者和业界工作者的新宠。