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The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework.
Features
- Around 150 Julia and Python models accessed through a uniform interface
- Pipelines and FeatureUnions
- Cross-validation
- Hyperparameter tuning
- DataFrames support
- Documentation available
Project Samples
Categories
Data VisualizationLicense
MIT LicenseFollow ScikitLearn.jl
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