Check out what's new with ML.NET Automated ML (AutoML), tooling, and notebooks!
Learn how to create a training pipeline for ML.NET using Azure ML and Azure Devops.
Check out what's new in ML.NET and Model Builder.
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This release of ML.NET and Model Builder brings numerous bug fixes and enhancements as well as new features, including config-based training and a redesigned Consume step.
Learn how to serve machine learning models from HTTP APIs using minimal configuration
This release of ML.NET Model Builder brings numerous bug fixes and enhancements as well as new features, including advanced data loading options and streaming training data from SQL.
The specification defines many floating point types, including: , , and . Most developers are familiar with (equivalent to in C#) and (equivalent to in C#). They provide a standard format to represent a wide range of values with a precision acceptable for many applications. .NET has always had and and with .NET 5 Preview 7, we've added a ne...
ML.NET is an open-source, cross-platform machine learning framework for .NET developers. It enables integrating machine learning into your .NET apps without requiring you to leave the .NET ecosystem or even have a background in ML or data science. ML.NET provides tooling (Model Builder UI in Visual Studio and the cross platform ML.NET CLI) that aut...
This post will show you how to train a custom image classification model in Azure to categorize flowers using ML.NET Model Builder. Then, you can leverage your existing .NET skills to consume the trained model inside a C# .NET Core console application. Best of all, little to no prior machine learning knowledge is required.
