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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.
Machine Learning in .NET Core. Contribute to SciSharp/scikit-learn.net development by creating an account on GitHub.
SciSharp provides ports and bindings to cutting edge Machine Learning frameworks like TensorFlow, Keras, PyTorch, Numpy and many more in .NET Core.
21 Δεκ 2017 · The more reliable and way more flexible way is to do the prediction in Python using sklearn and communicate with your C# program via files or (better) a web service. Olivier Grisel (one of the sklearn authors) concisely describes your options in this post.
4 Ιουλ 2020 · In this article, we’ll look at a better way to bridge the technology gap between Data Scientists and App Developers using the ONNX Model format and the ONNX Runtime. Specifically, we’ll show how you can build and train a model using Sci-kit Learn, then use that same model to perform real-time inference in a .NET Core Web API.
Keras.NET is a high-level neural networks API for C# and F# via a Python binding and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation.
5 Απρ 2022 · To deploy a machine learning trained model in a .NET application using ONNX files, the sklearn model is converted into a serialized string with the assistance of the skl2onnx library. Here ...
