google-cloud-pipeline-components
# Google Cloud Pipeline Components
[](https://github.com/kubeflow/pipelines/tree/master/components/google-cloud)
[](https://badge.fury.io/py/google-cloud-pipeline-components.svg)
[Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/build-pipeline?hl=en#google-cloud-components) (GCPC) provides predefined [KFP](https://www.kubeflow.org/docs/components/pipelines/) components that can be run on Google Cloud Vertex AI Pipelines and other KFP-conformant pipeline execution backends. You can compose the components together into pipelines using the [Kubeflow Pipelines SDK](https://pypi.org/project/kfp/).
## Documentation
### User documentation
Please see the [Google Cloud Pipeline Components user guide](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction).
### API documentation
Please see the [Google Cloud Pipeline Components API reference documentation](https://google-cloud-pipeline-components.readthedocs.io/).
### Release details
For details about previous and upcoming releases, please see the [release notes](https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/RELEASE.md).
## Examples
* [Train an image classification model using Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_images.ipynb).
* [Train a classification model using tabular data and Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/automl_tabular_classification_beans.ipynb).
* [Train a linear regression model using tabular data and Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb).
* [Train a text classification model using Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_text.ipynb).
* [Use the Google Cloud pipeline components to upload and deploy a model](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_model_train_upload_deploy.ipynb).
## Installation
### Requirements
- Python >= 3.7
- [A Google Cloud project with the Vertex API enabled.](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)
- An
[authenticated GCP account](https://cloud.google.com/ai-platform/docs/getting-started-keras#authenticate_your_gcp_account)
### Install latest release
Use the following command to install Google Cloud Pipeline Components from [PyPI](https://pypi.org/project/google-cloud-pipeline-components/).
```shell
pip install -U google-cloud-pipeline-components
```
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"description": "# Google Cloud Pipeline Components\n\n[](https://github.com/kubeflow/pipelines/tree/master/components/google-cloud)\n[](https://badge.fury.io/py/google-cloud-pipeline-components.svg)\n\n[Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/build-pipeline?hl=en#google-cloud-components) (GCPC) provides predefined [KFP](https://www.kubeflow.org/docs/components/pipelines/) components that can be run on Google Cloud Vertex AI Pipelines and other KFP-conformant pipeline execution backends. You can compose the components together into pipelines using the [Kubeflow Pipelines SDK](https://pypi.org/project/kfp/).\n\n## Documentation\n\n### User documentation\n\nPlease see the [Google Cloud Pipeline Components user guide](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction).\n\n### API documentation\nPlease see the [Google Cloud Pipeline Components API reference documentation](https://google-cloud-pipeline-components.readthedocs.io/).\n\n### Release details\nFor details about previous and upcoming releases, please see the [release notes](https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/RELEASE.md).\n\n## Examples\n* [Train an image classification model using Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_images.ipynb).\n* [Train a classification model using tabular data and Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/automl_tabular_classification_beans.ipynb).\n* [Train a linear regression model using tabular data and Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb).\n* [Train a text classification model using Vertex AI AutoML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_automl_text.ipynb).\n* [Use the Google Cloud pipeline components to upload and deploy a model](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/master/notebooks/official/pipelines/google_cloud_pipeline_components_model_train_upload_deploy.ipynb).\n\n## Installation\n\n### Requirements\n\n- Python >= 3.7\n- [A Google Cloud project with the Vertex API enabled.](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)\n- An\n [authenticated GCP account](https://cloud.google.com/ai-platform/docs/getting-started-keras#authenticate_your_gcp_account)\n\n\n### Install latest release\n\nUse the following command to install Google Cloud Pipeline Components from [PyPI](https://pypi.org/project/google-cloud-pipeline-components/).\n\n```shell\npip install -U google-cloud-pipeline-components\n```\n\n\n",
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