Jon Wood shows us how to install the C# Jupyter Kernel and then uses it to build a ML.NET AutoML experiment with the DataFrame package.

Installation instructions – https://github.com/dotnet/try/issues/408#issue-487051763

Notebook – https://github.com/jwood803/MLNetExamples/blob/master/MLNetExamples/Notebooks/Dataframe%20with%20AutoML.ipynb

Sample Notebook from Microsoft – https://github.com/dotnet/try/blob/master/NotebookExamples/csharp/Samples/HousingML.ipynb

.NET Core 3 will be a major milestone with tons of new features, performance updates and support for new workloads.

In this video, Richard Lander and Scott Hunter get together to discuss some of the highlights that developers can look forward to in this new release.

Useful Links

Good news for .NET developers who want to do more AI, but want to leverage their experience with C#.

Instead of glibly telling .NET developers to go learn Python, Microsoft is letting them know that they can now do machine learning work in the more familiar surroundings of the mainstream C# language. ML.NET makes this possible, and Microsoft has a GitHub repo with an array of samples to help .NET developers see how.

John Spaith is lead developer on the C SDK for Azure IoT. In the video below, watch him and Olivier Bloch go through the SDK usage and portability for IoT devices running Linux, Windows or real time OSs as well as microcontrollers.

 

In this episode of Visual Studio Toolbox, Ed Charbeneau discusses how a number of language features in C# support functional programming, a programming style that treats computation as the evaluation of mathematical functions and avoids changing state and mutable data.

Resources: