Dataset
Add a dataset instance prior to building a model
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Add a dataset instance prior to building a model
Last updated
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Within the Tensorleap platform, a Dataset Instance contains the Dataset Script and properties for reading and encoding the data that will later be used when training, evaluating and analyzing a model.
Additionally, store sensitive information and credentials securely with Secret Manager.
In order for the Tensorleap platform to read and encode the data, it must be supplied with a Dataset Script. The DatasetScript is stored within the Dataset Instance, at which the Dataset Block points and used as input/ground truth encoders.
More info about can be found at Dataset Script.
To integrate your data into the Tensorleap platform, you need to add a Dataset Instance. Once it is set and configured, you can use it with a model.
To add a Dataset Instance:
Click on the side menu, then Resources Management.
On the Resources Management window, under the Datasets section, click New Dataset.
On the Dataset Editor, select a Secret (see Secret Manager), and dataset name.
Enter the dataset script (see Dataset Script) into the Code Editor.
Click Save. This adds the dataset to the list on the lower left.
You can delete dataset instances that you do not use anymore in your projects from your list of Datasets. This will make the list in your account more manageable.
To delete a Dataset Instance:
Click the side menu, then Resources Management.
On the Resources Management window, under the Datasets section, look for the Dataset Instance to be deleted from the list.
When you find the Dataset, position your cursor over the record, then click and Delete Dataset.
