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SoleData.jl – Unstructured and Multimodal datasets

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In a nutshell

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!

About

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.