Easily boost your Scikit Learn Pipelines with powerful features, such as:
Scaling experiments on dask.
Wrapping data-points with metadata and passing them to the estimator.fit and estimator.transform methods.
Checkpointing data-points after each step of your pipeline.
Expressing database protocol as csv files and using them easily.
If you want to implement your own scikit-learn estimator, please, check out this link
- Samples, a way to enhance scikit pipelines with metadata
- Dask: Scale your scikit.learn pipelines
- File List Databases (CSV)
- Efficient pipelines with dask and xarray
- Python API for bob.pipelines