A project can have multiple datasets, each used to train a separate model. You can get a list of the available datasets and can delete datasets you no longer need.
For information about creating a dataset and importing data into it, see Creating datasets and importing data.
Listing datasets
A project can include numerous datasets. This section describes how to retrieve a list of the available datasets for a project.
To see a list of the available datasets using the AutoML Natural Language UI, click the Datasets link at the top of the left navigation menu.
To see the datasets for a different project, select the project from the drop-down list in the upper right of the title bar.
REST & CMD LINE
Before using any of the request data below, make the following replacements:
- project-id: your project ID
- location-id: the location for the resource,
us-central1
for the Global location oreu
for the European Union
HTTP method and URL:
GET https://automl.googleapis.com/v1/projects/project-id/locations/location-id/datasets
To send your request, expand one of these options:
You should receive a JSON response similar to the following:
{ "datasets": [ { "name": "projects/434039606874/locations/us-central1/datasets/356587829854924648", "displayName": "test_dataset", "createTime": "2018-04-26T18:02:59.825060Z", "textClassificationDatasetMetadata": { "classificationType": "MULTICLASS" } }, { "name": "projects/434039606874/locations/us-central1/datasets/3104518874390609379", "displayName": "test", "createTime": "2017-12-16T01:10:38.328280Z", "textClassificationDatasetMetadata": { "classificationType": "MULTICLASS" } } ] }
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Export a dataset
You can export a CSV file with all a dataset's information to a Cloud Storage bucket. The exported CSV file has the same format as the training data import CSV.
To export a dataset:
Select the dataset you want to export documents into from the Datasets page.
Click the Export data option at the top of the Dataset details page.
Navigate to the Cloud Storage bucket where you want to write the export CSV file.
Click Export CSV.
You will receive an email when the data export process has completed.
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Deleting a dataset
To delete a dataset in the AutoML Natural Language UI:
Click the three-dot menu at the far right of the dataset you want to delete and select Delete dataset.
Click Delete in the confirmation dialog box.
REST & CMD LINE
Before using any of the request data below, make the following replacements:
- project-id: your project ID
- location-id: the location for the resource,
us-central1
for the Global location oreu
for the European Union - dataset-id: your dataset ID
HTTP method and URL:
DELETE https://automl.googleapis.com/v1/projects/project-id/locations/location-id/datasets/dataset-id
To send your request, expand one of these options:
You should receive a JSON response similar to the following:
{ "name": "projects/434039606874/locations/us-central1/operations/4422270194425422927", "metadata": { "@type": "type.googleapis.com/google.cloud.automl.v1beta1.OperationMetadata", "progressPercentage": 100, "createTime": "2018-04-27T02:33:02.479200Z", "updateTime": "2018-04-27T02:35:17.309060Z" }, "done": true, "response": { "@type": "type.googleapis.com/google.protobuf.Empty" } }
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Java
Node.js
Go
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Ruby