scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed.
Scikit-learn contains a collection of classic ML models that can be used to solve various practical tasks: classification, regression, data points clustering, etc. using for instance SVM, logistic regression, decision tree, isolation forest, etc.
Model deployment from scikit-learn is simple to achieve by exporting your sklearn model to ONNX using the skl2onnx package.
After obtaining a clean ONNX graph that adheres to our requirements, you can upload it to the Nx AI cloud for deployment.
