SoleData provides a machine learning oriented data layer on top of DataFrames.jl for:
- Instantiating and manipulating multimodal datasets for (un)supervised machine learning;
- Dealing with (un)structured data (e.g., graphs, images, time-series, etc.);
- Describing datasets via basic statistical measures;
- Saving to/loading from npy/npz format, as well as a custom CSV-based format (with interesting features such as lazy loading of datasets);
- Performing basic data processing operations (e.g., windowing, moving average, etc.).
If you are used to dealing with unstructured/multimodal data, but cannot find the right tools in Julia, you will find SoleFeatures.jl useful!
The package is developed by the ACLAI Lab @ University of Ferrara.
SoleData.jl was originally built as the data layer for Sole.jl, an open-source framework for symbolic machine learning.