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BigML in Chinese
Feb2018
Image of BigML in Chinese

The BigML Team is excited to release the BigML Dashboard in Chinese. Since its very beginning, BigML has strived to make Machine Learning Beautifully Simple for Everyone (机器学习美观简单人人用). Today our journey reached another milestone by allowing over 1 billion people to use the BigML platform in their native language.

You can watch this video to check out the BigML Dashboard in Chinese

chinese languages dashboard web
Organizations
Jan2018
Image of Organizations

Machine Learning projects usually involve several members from different teams that need to work on the same project and/or visualize the same resources. Now, BigML offers organizations, a convenient collaborative workspace that makes your life easier and your work more efficient, where several users can work on the same projects from different accounts at different permission levels. Break down silos and let us help you to adopt Machine Learning across your entire corporate structure.

Create a new organization or learn more about it.

organizations collaboration projects permissions roles web
Shared Resources Cloning
Jan2017
Image of Shared Resources Cloning

Now, you can easily clone datasets, models and scripts, from other users into your BigML account. Provided that a user shares a resource using the sharing link and the cloning capability is enabled, any other user with access to the link will be able to include this resource in their BigML account.

This new feature will allow you to fully use the shared resources. For example, when another user shares a dataset using the sharing link, it is in "view only" mode, so you can not perform any actions such as creating new models, exporting it, sampling it, etc. Now, by cloning it, you will be able to perform all BigML actions available for datasets.

resources cloning sharing link dashboard web
Dataset Comparison
Jan2015
Image of Dataset Comparison

This is another simple but useful application we have released into our new BigML Labs. It allows users to compare side by side two different datasets. Check it out here.

dataset winter2015 labs web
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