MultiData.jl

Multimodal datasets for Machine-Learning
Author aclai-lab
Popularity
3 Stars
Updated Last
2 Months Ago
Started In
February 2024

MultiData.jl – Multimodal datasets

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In a nutshell

MultiData provides a machine learning oriented data layer on top of DataFrames.jl for:

  • Instantiating and manipulating multimodal datasets for (un)supervised machine learning;
  • 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.).

About

The package is developed by the ACLAI Lab @ University of Ferrara.

MultiData.jl was originally built for representing multimodal datasets in Sole.jl, an open-source framework for symbolic machine learning.