Cool!
On Friday, March 18, 2016 at 5:11:47 PM UTC+1, Cedric St-Jean wrote: > > I'm happy to announce ScikitLearn.jl > <https://github.com/cstjean/ScikitLearn.jl> and ScikitLearnBase.jl > <https://github.com/cstjean/ScikitLearnBase.jl>: a library pair that > brings the scikit-learn interface to Julia. > > > *Highlights* > > - Around 150 machine learning and statistical models accessed through > a uniform interface > - Pipelines and FeatureUnions > - Cross-validation > - Model selection (hyperparameter tuning) > - Feature extraction (text processing, one hot encoding, etc.) > > Check out the documentation > <http://scikitlearnjl.readthedocs.org/en/latest/>, quick start guide > <http://scikitlearnjl.readthedocs.org/en/latest/quickstart/> and example > gallery > <https://github.com/cstjean/ScikitLearn.jl/blob/master/docs/examples.md>. > > > ScikitLearn.jl uses PyCall.jl for Python models, but the "glue" (eg. > Pipelines) was translated to make it possible to implement models in Julia. > For instance, one might pipeline a factor analysis model from Python into a > deep learning model written in Julia, and use grid search to optimize its > hyperparameters. > > > Any Julia type that implements the scikit-learn interface > <https://github.com/cstjean/ScikitLearnBase.jl> can be used with this > framework. If you have any issue supporting the interface for your library, > ping me @cstjean. > > > Best, > > Cédric St-Jean >
