MLDev: Data Science Experiment Automation and Reproducibility Software
Anton Khritankov, Nikita Pershin, Nikita Ukhov, Artem Ukhov

TL;DR
MLDev is an open source software that automates data science experiments, enhances reproducibility, and integrates various tools, addressing key challenges in research automation with promising initial results.
Contribution
Introduces an extensible experiment model and a prototype software package that improves automation and integration in data science experiments.
Findings
Prototype software demonstrates effective experiment automation.
Comparison shows advantages over existing tools.
Promising results in experiment reproducibility and integration.
Abstract
In this paper we explore the challenges of automating experiments in data science. We propose an extensible experiment model as a foundation for integration of different open source tools for running research experiments. We implement our approach in a prototype open source MLDev software package and evaluate it in a series of experiments yielding promising results. Comparison with other state-of-the-art tools signifies novelty of our approach.
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Taxonomy
TopicsScientific Computing and Data Management · Machine Learning and Data Classification · Data Stream Mining Techniques
