TENSORFLOW in English translation

• tensorflow

Examples of using Tensorflow in Chinese and their translations into English

AWS支持所有主流机器学习框架，包括ApacheMXNet、TensorFlow和Caffe2，以便您可以引入或开发您选择的任何模型。
AWS supports all the major machine learning frameworks, including TensorFlow, Caffe2, and Apache MXNet, so that you can bring or develop any model you choose.

TensorFlow的设计目的是使并行和多GPU上的深度神经网络更容易训练，但它也支持传统的算法。
TensorFlow was designed to make it easy to train deep neural networks in parallel and on multiple GPUs, but it also supports traditional algorithms.

TensorFlowExtended，是一个端到端平台，用于在大型生产环境中准备数据、培训、验证和部署模型。
TensorFlow Extended is an end-to-end platform for preparing data, training, validating, and deploying models in large production environments.

GoogleTensorFlow已经成为金融公司和研究机构的宠儿，但它的技术可能很吓人，学习曲线也很陡峭。
Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep.

与HTML类似，Tensorflow是用于表示某种类型的计算抽象（称为“计算图”）的框架。
Similarly to HTML, Tensorflow is a framework for representing a certain type of computational abstraction(known as“computation graphs”).

在下文中，我假设读者已经准备好Go环境，并按照README中的说明编译并安装了Tensorflow绑定。
In the following, I suppose that the reader has its Go environment ready and the Tensorflow bindings compiled and installed as explained in the README.

我们需要安装RaspbianStretch9，因为在运行Raspbian9时，TensorFlow1.9正式支持树莓派。
We need Raspbian Stretch 9 installed, since TensorFlow 1.9 officially supports the Raspberry Pi if you are running Raspbian 9.

如前所述，许多专业数据科学家选择使用开源机器学习工具，如TensorFlow，ApacheSpark的MLlib或Caffe。
As already mentioned, many professional data scientists choose to use open source machine learning tools, such as TensorFlow, Apache Spark's MLlib or Caffe.

为了处理上面提到的挑战，Duplex的核心是一个RNN网络，它是由TensorFlowExtended（RFX）构建的。
In order to deal with the challenges mentioned above, the heart of Duplex is a RNN network, which is built by TensorFlow Extended(RFX).

Chellapilla：对于起步者，我建议选择R，scikit-learn，NLTK/spaCy和TensorFlow。
Chellapilla: For someone starting out, I would suggest picking up R, scikit-learn, NLTK/spaCy, and TensorFlow.

在2018年的TensorFlow开发者峰会上，Google宣布了他们的机器学习框架TensorFlow的JavaScript实现，称为TensorFlow.js。
At the TensorFlow Dev Summit 2018, Google announced the JavaScript implementation of TensorFlow, their machine learning framework, called TensorFlow. js.

AWS深度学习AMI自带预配置的流行框架，例如ApacheMXNet、TensorFlow、Caffe和Keras。
The AWS Deep Learning AMI comes pre-configured with popular frameworks such as Apache MXNet, TensorFlow, Caffe, and Keras.

Chellapilla：对于起步者，我建议选择R，scikit-learn，NLTK/spaCy和TensorFlow。
Chellapilla: For someone starting out, I would suggest picking up R, scikit-learn, NLTK/spaCy, and TensorFlow.

阅读本文后，您将能够理解神经网络的应用，并使用TensorFlow来解决现实生活中的问题。
After reading this article you will be able to understand application of neural networks and use TensorFlow to solve a real life problem.

下面的代码是一位TensorflowPython用户第一次尝试时会写的代码。
The code below is the first attempt that a Tensorflow Python bindings user would make.

通过利用一些像TensorFlow等的开源框架，这些解决方案将大大降低创建复杂深度学习系统的工作量、时间以及成本。
Making use of open-source frameworks such as TensorFlow, these solutions will dramatically reduce the effort, time, and costs of creating complex deep learning systems.

Sonnet是一个建立在TensorFlow之上的库，用于构建复杂的神经网络.
Sonnet is a library built on top of TensorFlow for building complex neural networks.

如今它们已经被TensorFlow（经常是以高层APIKeras的形式被使用）、CNTK、Caffe2和ApacheMXNet所取代。
By now they have been superseded by TensorFlow, often used via its high level API Keras, CNTK, Caffe 2, and Apache MxNet.

Python是TensorFlow支持的第一种客户端语言，目前支持的功能最多。
Python was the first client language supported by TensorFlow and currently supports the most features.

Feeding是TensorFlowSessionAPI的一种机制，它允许你在运行时用不同的值替换一个或多个tensor的值。
Feeding is a mechanism in the tf. Session API that allows you to substitute different values for one or more tensors at run time.