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snsn1984 2016-05-09 08:54:30 浏览732


Machine Learning in the Cloud, with TensorFlow

Wednesday, March 23, 2016


At Google, researchers collaborate closely with product teams, applying the latest advances in Machine Learning to existing products and services - such as speech recognition in the Google app,search in Google Photos and the Smart Reply feature in Inbox by Gmail - in order to make them more useful. A growing number of Google products are using TensorFlow, our open source Machine Learning system, to tackle ML challenges and we would like to enable others do the same.


Today, at GCP NEXT 2016, we announced the alpha release of Cloud Machine Learning, a framework for building and training custom models to be used in intelligent applications. 
今天,在GCP NEXT 2016上,我们宣布正式发布云机器学习的alpha版本,它是一个框架,这个框架将用来构建和训练客户模型,这些客户模型将应用在人工智能应用程序中。
Machine Learning projects can come in many sizes, and as we’ve seen with our open source offering TensorFlow, projects often need to scale up. Some small tasks are best handled with a local solution running on one’s desktop, while large scale applications require both the scale and dependability of a hosted solution. Google Cloud Machine Learning aims to support the full range and provide a seamless transition from local to cloud environment.


The Cloud Machine Learning offering allows users to run custom distributed learning algorithms based on TensorFlow. In addition to the deep learning capabilities that power Cloud Translate API,Cloud Vision API, and Cloud Speech API, we provide easy-to-adopt samples for common tasks like linear regression/classification with very fast convergence properties (based on the SDCAalgorithm) and building a custom image classification model with few hundred training examples (based on the DeCAF algorithm).

云机器学习提供了允许用户在TensorFlow的基础上运行客户的分布式学习算法的功能。在深度学习的容量之上,增强了Cloud Translate API,Cloud Vision API, and Cloud Speech API,我们提供了一些易于用于常用任务中的例子,比如:采用非常快的趋于一致属性的linear regression/classification(基于SDCA算法)和用几百个训练例子构建一个客户图像分类模型

We are excited to bring the best of Google Research to Google Cloud Platform. Learn more about this release and more from GCP Next 2016 on the Google Cloud Platform blog.
我们非常兴奋的把Google研究的最好的内容带到了Google云平台上。希望更多的了解这次发布和GCP Next 2016更多的内容,可以到Google云平台博客。