Gretel Smart-Seeding is auto-complete for your data

Smart-seeding is a feature that enables synthetic data models to auto-complete partial records and text. It has been used in two challenging use cases for synthetic data: removing bias from datasets and generating synthetic time-series data. Gretel has released two new blueprints that utilize smart-seeding, automating the process of recreating time series data with seasonal patterns, reducing biases in ML datasets by equalizing minority class representation, and creating synthetic data with the same shape as original data while preserving vital portions of each row. The Time Series Data blueprint trains synthetic time-series models on trends in data, while the General Smart-Seeding blueprint allows users to take partial values from their training dataset for synthesis.