model_garden/notebooks/official/feature_store

Streaming ingestion SDK

Learn how to ingest features from a `Pandas DataFrame` into your Vertex AI Feature Store using `write_feature_values` method from the Vertex AI SDK.

The steps performed include:

- Create `Feature Store`
- Create new `Entity Type` for your `Feature Store`
- Ingest feature values from `Pandas DataFrame` into `Feature Store`'s `Entity Types`.

   Learn more about Vertex AI Feature Store.

Using Vertex AI Feature Store with Pandas Dataframe

Learn how to use `Vertex AI Feature Store` with pandas Dataframe.

The steps performed include:

- Ingest Feature values from Pandas DataFrame into Feature Store's Entity types.
- Read Entity feature values from Online Feature Store into Pandas DataFrame.
- Batch serve feature values from your Feature Store into Pandas DataFrame.


- Online serving with updated feature values.
- Point-in-time correctness to fetch feature values for training.

   Learn more about Vertex AI Feature Store.

Online and Batch predictions using Vertex AI Feature Store

Learn how to use `Vertex AI Feature Store` to import feature data, and to access the feature data for both online serving and offline tasks, such as training.

The steps performed include:

- Create featurestore, entity type, and feature resources.
- Import feature data into `Vertex AI Feature Store` resource.
- Serve online prediction requests using the imported features.
- Access imported features in offline jobs, such as training jobs.
- Use streaming ingestion to ingest small amount of data.

   Learn more about Vertex AI Feature Store.