Skrub is an open source package that simplifies machine-learning with dataframes by providing a variety of tools to explore, prepare and feature-engineer dataframes so they can be integrated into scikit-learn pipelines. Skrub DataOps allow to build extensive, multi-table wrangling plans, explore hyperparameter spaces, and export the resulting objects for deployment.
The talk showcases various use cases where skrub can simplify the job of a data scientist from data preparation to deployment, through code examples and demonstrations.