hops-transformations

What problem does it solve?

This Skill simplifies the creation and application of transformations in Hopsworks, enabling users to apply built-in and custom transformations efficiently.

Core Features & Use Cases

• Model-Dependent Transforms: Apply transformations like scalers, encoders, and imputers that learn from training data.
• On-Demand Transforms: Compute transformations at request time for use in feature groups.
• Custom UDFs: Create custom transformations using Python UDFs for specific needs.
• Use Case: If you need to preprocess data for machine learning models in Hopsworks, this Skill provides the tools to handle scaling, encoding, and imputation tasks.

Quick Start

Define a custom transformation with a Python UDF and apply it to a feature view in Hopsworks.