Information for each feature of your dataset is presented in columns. Each column displays the name of a feature, its shape, and the distribution of values. You can also see a preview of the values for the first examples.
Note that to speed up processing, the platform only analyzes a fraction of the examples contained in a dataset. This has two consequences:
The information presented has a small degree of approximation.
The shape and the encodings available for a feature are determined only from the analyzed examples.
Every example must have its features compatible with the shape and encoding indicated in the dataset’s version, or running your experiment will fail. If your experiment fails because of incompatible examples, you can click the icon under the experiment’s name to get more information about the problematic examples.
Collaborating with your team
Colleagues can work with the same datasets as everything securely stored in the cloud.