SciSharp STACK Web Portal

This repo contains the source code for http://scisharpstack.org

Comprehensive list of all Projects

Stable or Beta

• TensorFlow.NET .NET Standard bindings for TensorFlow
• NumSharp Pure C# implementation of NumPy
• Keras.NET Keras.NET is a high-level neural networks API for C#/F# with Python Binding and capable of running on top of TensorFlow, CNTK, or Theano.
• Numpy.NET C#/F# bindings for NumPy - a fundamental library for scientific computing, machine learning and AI
• ICSharpCore Jupyter kernel in C# .NET Core which is the standard interface for SciSharp STACK.
• SharpCV A image library combines OpenCV and NumSharp together. SharpCV returns Mat object with NDArray supported.

Related technologies

• .NET Interactive Notebooks Jupyter notebooks for C# and F#. Share code, explore data, write, and learn across your apps in ways you couldn't before.
• Plotly.NET A .NET interface for plotly.js written in F#
• Dash.NET A .NET interface to Dash- the most downloaded framework for building ML & data science web apps
• FsLab An F# Community incubation space for data science

Referenced by:

• https://medium.com/dev-genius/tensorflow-basic-setup-for-net-developers-d56bfb0af40e
• https://www.youtube.com/watch?v=NpZP_TWhq04&t=155s
• https://medium.com/machinelearningadvantage/run-tensorflow-machine-learning-code-in-c-with-almost-no-changes-77f7b629389
• https://libinjoseph.com/2019/technologies-to-watch-out/
• https://devblogs.microsoft.com/dotnet/announcing-ml-net-1-4-preview-and-model-builder-updates-machine-learning-for-net/
• https://www.meetup.com/Frederick-NET-Meetup/events/263752705/
• https://devblogs.microsoft.com/cesardelatorre/training-image-classification-recognition-models-based-on-deep-learning-transfer-learning-with-ml-net/
• https://www.youtube.com/watch?v=sN9e-Fj4NuI&t=317m39s
• http://blog.itpub.net/69946223/viewspace-2661203/
• https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/image-classification-api-transfer-learning
• https://devblogs.microsoft.com/dotnet/announcing-ml-net-1-4-global-availability-machine-learning-for-net/