Get started with AI using ML.Net and Model Builder

Machine is an important tool for modern application development. We’ve gone from the cold depths of an AI winter to an explosion of new neural networks and models, building on the hyperscale compute capabilities of the cloud and on the requirements of big services. If you’re an AI researcher it’s an exciting time, with new discoveries and new tools arriving weekly.

But that’s only part of the story. Far more exciting is the democratization of machine learning. Research is a good thing, but it’s far better to the results of that research into action and into the hands of developers. APIs like Microsoft’s Azure Cognitive Services are one way to do this, but not every application has a permanent connection to Azure, so it’s important to have ML tools that build into our everyday development environments and tools.

Introducing ML.Net

That’s where ML.Net comes in. It’s Microsoft’s open source, cross-platform machine learning tool for .Net and .Net Core, targeting .Net Standard, running on Windows, Mac OS, and Linux systems. It’s extensible, so it works with not only Microsoft’s own ML tooling but also with other frameworks such as Google’s TensorFlow and the ONNX cross-platform export technology. By supporting as wide a selection of frameworks as possible, it gives you the option to pick and choose the ML models that are closest to your needs, fine tuning them to fit.

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