P
Peter Prettenhofer
Researcher at Bauhaus University, Weimar
Publications - 21
Citations - 78947
Peter Prettenhofer is an academic researcher from Bauhaus University, Weimar. The author has contributed to research in topics: Web search query & Python (programming language). The author has an hindex of 10, co-authored 21 publications receiving 63936 citations. Previous affiliations of Peter Prettenhofer include Graz University of Technology.
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Journal Article
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +15 more
TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
Posted Content
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Andreas Müller,Joel Nothman,Gilles Louppe,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +18 more
TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
Posted Content
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck,Gilles Louppe,Mathieu Blondel,Fabian Pedregosa,Andreas Mueller,Olivier Grisel,Vlad Niculae,Peter Prettenhofer,Alexandre Gramfort,Jaques Grobler,Robert Layton,Jake Vanderplas,Arnaud Joly,Brian Holt,Gaël Varoquaux +14 more
TL;DR: Scikit-learn as mentioned in this paper is a machine learning library written in Python, which is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts.
Proceedings Article
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck,Gilles Louppe,Mathieu Blondel,Fabian Pedregosa,Andreas Mueller,Olivier Grisel,Vlad Niculae,Peter Prettenhofer,Alexandre Gramfort,Jaques Grobler,Robert Layton,Jake Vanderplas,Arnaud Joly,Brian Holt,Gaël Varoquaux +14 more
TL;DR: Scikit-learn as discussed by the authors is a machine learning library written in Python, which is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts.
Proceedings Article
Cross-Language Text Classification Using Structural Correspondence Learning
Peter Prettenhofer,Benno Stein +1 more
TL;DR: A new approach to cross-language text classification that builds on structural correspondence learning, a recently proposed theory for domain adaptation, is presented, using unlabeled documents, along with a simple word translation oracle, in order to induce task-specific, cross-lingual word correspondences.