Microsoft Takes Infer.NET Machine Learning Framework to Open Source
One of the latest Microsoft creations to be taken open source is a cutting-edge project in the booming artificial intelligence (AI) space, called Infer.NET.
The cross-platform framework for model-based machine learning is now available on GitHub under an MIT license, free for use in commercial applications.
With model-based machine learning, instead of providing a number of models that the data may (or may not) fit into, the goal is instead to provide a framework that can support a wide variety of data models that can be tailored for one particular project. (Microsoft offers a free book explaining model-based machine learning here.)
And that's how Infer.NET works, according to Microsoft Research, which started the project back in 2004. The framework builds a custom machine learning algorithm directly from that model you provide: "This means that instead of having to map your problem onto a pre-existing learning algorithm that you've been given, Infer.NET actually constructs a learning algorithm for you," the company explained.
Infer.NET was featured in a keynote presentation this week (Oct. 9) at the Visual Studio Live! conference in San Diego, where it was discussed by Microsoft program managers Beth Massi and Jon Galloway.
Massi described Infer.NET as a "sister project" to ML.NET more geared to projects such as statisticl analysis. "They work with, you bring your own models to them," Galloway said. "So where with something like ML.NET you kind of adapt your patterns to their model system, with Infer, you can basically say, 'Infer, check out my models,' and it figures stuff out."
Several other aspects of Infer.NET set it apart, Microsoft Research states, including its use of probabilistic programming, deterministic inference algorithms and the way it supports online Bayesian inference.
Like machine learning itself, the platform has transformed from primarily research-based uses cases to more and more commercial applications. Even so, it's still regularly used in academic projects (a list of papers can be found here).
According to Microsoft, along with open sourcing Infer.NET, it will no longer stand alone: "Infer.NET will become a part of ML.NET – the machine learning framework for .NET developers. We have already taken several steps towards integration with ML.NET, like setting up the repository under the .NET Foundation and moving the package and namespaces to Microsoft.ML.Probabilistic. Infer.NET will extend ML.NET for statistical modeling and online learning."
"The Infer.NET team is looking forward to engaging with the open-source community in developing and growing the framework further," Microsoft Research continued.
Becky Nagel is the vice president of Web & Digital Strategy for 1105's Converge360 Group, where she oversees the front-end Web team and deals with all aspects of digital strategy. She also serves as executive editor of the group's media Web sites, and you'll even find her byline on PureAI.com, the group's newest site for enterprise developers working with AI. She recently gave a talk at a leading technical publishers conference about how changes in Web technology may impact publishers' bottom lines. Follow her on twitter @beckynagel.