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A Survey of Open Source Automation Tools for Data Science Predictions

Machine Learning 2022-08-26 v1
Authors: Nicholas Hoell
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Abstract

We present an expository overview of technical and cultural challenges to the development and adoption of automation at various stages in the data science prediction lifecycle, restricting focus to supervised learning with structured datasets. In addition, we review popular open source Python tools implementing common solution patterns for the automation challenges and highlight gaps where we feel progress still demands to be made.

Keywords

software library data warehousing scholarly communication

Cite

@article{arxiv.2208.11792,
  title  = {A Survey of Open Source Automation Tools for Data Science Predictions},
  author = {Nicholas Hoell},
  journal= {arXiv preprint arXiv:2208.11792},
  year   = {2022}
}

Comments

56 pages, 1 figure, 2 tables

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