Automating data science

Communications of the ACM, vol. 65, pp. 76–87

Abstract

Given the complexity of data science projects and related demand for human expertise, automation has the potential to transform the data science process.

Authors 6

1. Tijl De Bie

   Ghent University

   Affiliation as printed

   Ghent University, Belgium

2. Luc De Raedt

   Örebro University · KU Leuven

   Affiliation as printed

   KU Leuven, Belgium and Örebro University, Sweden

3. José Hernández‐Orallo

   Universitat Politècnica de València

   Affiliation as printed

   Universitat Politècnica de València, Spain

4. Holger H. Hoos Aachen

   Leiden University · University of British Columbia

   Affiliation as printed

   Leiden University, The Netherlands and University of British Columbia in Vancouver, Canada

5. Padhraic Smyth

   University of California, Irvine

   Affiliation as printed

   University of California, Irvine

6. Christopher K. I. Williams

   The Alan Turing Institute · University of Edinburgh

   Affiliation as printed

   University of Edinburgh, U.K and Alan Turing Institute, London, U.K