arXiv · 2004.11113
Human-Machine Collaboration for Democratizing Data Science
Abstract
Everybody wants to analyse their data, but only few posses the data science expertise to to this. Motivated by this observation we introduce a novel framework and system \textsc{VisualSynth} for human-machine collaboration in data science. It wants to democratize data science by allowing users to interact with standard spreadsheet software in order to perform and automate various data analysis tasks ranging from data wrangling, data selection, clustering, constraint learning, predictive modeling and auto-completion. \textsc{VisualSynth} relies on the user providing colored sketches, i.e., coloring parts of the spreadsheet, to partially specify data science tasks, which are then determined and executed using artificial intelligence techniques.
Explore related subjects
Keep this discovery
Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt. 2020-04-23. Human-Machine Collaboration for Democratizing Data Science. https://arxiv.org/abs/2004.11113
Cite the original work for its findings. Save a collection to share your selection of sources.