Scikit-learn
Institut national de recherche en sciences et technologies du numérique · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · +2 more institutions
Abstract
Machine learning is a pervasive development at the intersection of statistics and computer science. While it can benefit many data-related applications, the technical nature of the research literature and the corresponding algorithms slows down its adoption. Scikit-learn is an open-source software project that aims at making machine learning accessible to all, whether it be in academia or in industry. It benefits from the general-purpose Python language, which is both broadly adopted in the scientific world, and supported by a thriving ecosystem of contributors. Here we give a quick introduction to scikit-learn as well as to machine-learning basics.
Citation impact
- FWCI
- 5.79
- Percentile
- 100%
- References
- 19
Authors
6- GVGaël VaroquauxCorresponding
Institut national de recherche en sciences et technologies du numérique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives
- LBLars Buitinck
University of Amsterdam
- GLGilles Louppe
University of Liège
- OGOlivier Grisel
Institut national de recherche en sciences et technologies du numérique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives
- FPFabian Pedregosa
Institut national de recherche en sciences et technologies du numérique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives
Topics & keywords
- Thriving
- Python (programming language)
- Computer science
- Artificial intelligence
- Software engineering
- Machine learning
- Data science
- Programming language