MLDev: Data Science Experiment Automation and Reproducibility Software
This addresses the problem of experiment automation and reproducibility for data scientists, but appears incremental as it builds on existing open-source tools.
The paper tackles the challenge of automating experiments in data science by proposing an extensible experiment model and implementing it in the MLDev software package, with evaluation showing promising results and novelty compared to state-of-the-art tools.
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.