azureml-featurestore 0.1.0b4

Azure Machine Learning Feature Store SDK

# Azure Machine Learning Feature Store Python SDK

The azureml-featurestore package is the core SDK interface for Azure ML Feature Store. This SDK works along the azure-ai-ml SDK to provide the managed feature store experience.

## Main features in the azureml-featurestore package - Develop feature set specification in Spark with the ability for feature transformation. - List and get feature sets defined in Azure  ML Feature Store. - Generate and resolve feature retrieval specification. - Run offline feature retrieval with point-in-time join.

## Getting started

You can install the package via ` pip install azureml-featurestore `

To learn more about Azure ML managed feature store visit https://aka.ms/featurestore-get-started

# Change Log

## 0.1.0b4 (2023.08.28)

New Features:

• [Public preview] Added custom feature source. Custom feature source supports customized source process code script with a user defined dictionary as input.

• [Public preview] Added csv feature source, deltatable feature source, mltable feature source, parquet feature source as new feature source experience. Previous feature source usage compatibility will be deprecated in 6 months.

• Bug fixes

Breaking changes: - Moved init_online_lookup, shutdown_online_lookup and get_online_features out of FeatureStoreClient, and into the module as standalone functions. - get_online_features contract changed from accepting (for the observation_data argument) and returning pandas.DataFrame to accepting (as the observation_data argument) and returning pyarrow.Table.

Other changes: - Moved online feature store support into public preview.

## 0.1.0b3 (2023.07.10)

• Various bug fixes

## 0.1.0b2 (2023.06.13)

New Features:

• [Private preview] Added online store support. Online store supports materialization and online feature values retrieval from Redis cache for batch scoring.

• Various bug fixes

## 0.1.0b1 (2023.05.15)

New Features:

Initial release.