The Hopsworks Feature Store is a platform for managing and serving features for machine learning that also integrates with Amazon SageMaker.
- Available as open-source, Enterprise, or as a managed platform on AWS (www.hopsworks.ai)
- API support for ingesting features as dataframes (Spark/Pandas) with data validation and feature statistics (Deequ)
- Catalog and tag features and search for them in Hopsworks
- Feature computation either in Hopsworks or external (Databricks, AWS EMR, etc)
- Offline feature store with scale-out storage of feature data (Apache Hive + HopsFS - with data stored in S3 on AWS) and easy generation of train/test data on S3/HDFS/HopsFS
The Enterprise Feature Store also includes integration with SageMaker. SageMaker, users can write Python or Scala programs to compute features and register them in Hopsworks, browse and inspect features, and create train/test datasets.
During this webinar we will introduce the concept of a Feature Store and how it helps manage data for AI. We will walk-through the Hopsworks Feature Store, introducing its concepts and how you can use it from Sagemaker for feature engineering, as a feature registry, for creating train/test datasets for ML, and as an online Feature Store to build feature vectors for online applications with low latency.