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漂流瓶终于彻底拜拜 微信7.0.4新版体验
微信漂流瓶被玩坏了 聊聊漂流瓶里那些事
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借贷宝:停止催收百名裸条女大学生 未满23岁将不得借贷
京东白条多地频现盗刷 消费者遭催收公司“逼债”
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Google-led Kubeflow, machine learning for Kubernetes, begins to take shape
谷歌领导的KuBeFube,机器学习为Kubernetes,开始成形

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编辑: 1   作者: Techcrunch   时间: 2018/10/30 23:57:14  

Ever since Google created Kubernetes as an open source container orchestration tool, it has seen it blossom in ways it might never have imagined. As the project gains in popularity, we are seeing many adjunct programs develop. Today, Google announced the release of version 0.1 of the Kubeflow open source tool, which is designed to bring machine learning to Kubernetes containers.

While Google has long since moved Kubernetes into the Cloud Native Computing Foundation, it continues to be actively involved, and Kubeflow is one manifestation of that. The project was only first announced at the end of last year at Kubecon in Austin, but it is beginning to gain some momentum.

David Aronchick, who runs Kubeflow for Google, led project management for Kubernetes and Google Kubernetes Engine (GKE) for 2.5 years before moving to Kubeflow. He says the idea behind the project is to enable data scientists to take advantage of running machine learning jobs on Kubernetes clusters. Kubeflow lets machine learning teams take existing jobs and simply attach them to a cluster without a lot of adapting.

With today's announcement, the project begins to move ahead, and according to a blog post announcing the milestone, brings a new level of stability, while adding a slew of new features that the community has been requesting. These include Jupyter Hub for collaborative and interactive training on machine learning jobs and Tensorflow training and hosting support, among other elements.

Aronchick emphasizes that as an open source project you can bring whatever tools you like, and you are not limited to Tensorflow, despite the fact that this early version release does include support for Google's machine learning tools. You can expect additional tool support as the project develops further.

In just over 4 months since the original announcement, the community has grown quickly with over 70 contributors, over 20 contributing organizations along with over 700 commits in 15 repositories. You can expect the next version, 0.2, sometime this summer.