A Survey of Open Source Automation Tools for Data Science Predictions
Nicholas Hoell
TL;DR
This survey reviews open source Python tools for automating supervised data science tasks, discusses challenges in adoption, and identifies gaps for future development.
Contribution
It provides a comprehensive overview of existing automation tools and highlights areas needing further progress in open source data science automation.
Findings
Identifies key challenges in adopting automation in data science.
Reviews popular open source tools for supervised learning automation.
Highlights gaps and future directions for tool development.
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.
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Taxonomy
TopicsComputational Physics and Python Applications · Machine Learning and Data Classification · Scientific Computing and Data Management