ML.NET Machine Learning Framework Update Addresses Usability and Stability

After hitting version 1.0 last month, Microsoft's open source, cross-platform machine learning framework ML.NET has received its first update, adding functionality and addressing developer concerns about usability and stability in the Model Builder component.

ML.NET 1.1, consisting of a Visual Studio UI tool called Model Builder and a command-line interface (CLI), works with AutoML to help C# and F# coders create machine learning models.

By adding machine learning functionality to .NET applications, they can use available data to make predictions and address use cases such as:

  • Classification/categorization
  • Regression/predict continuous values
  • Anomaly detection
  • Recommendations
  • Sentiment analysis
  • Object detection

New in ML.NET 1.1, as detailed in a June 11 blog post, are:

  • Preview of support for in-memory "image type" in IDataview: Developers can now load in-memory images and process them directly instead of having to specify file paths for images stored on a hard drive.
  • Preview of Anomaly Detection algorithm: A new Anomaly Detection algorithm named SrCnnAnomalyDetection has been added to the Time Series NuGet package, without requiring any prior training for use.
  • Preview of Time Series Forecasting components: Also added to the Time Series NuGet package, a new component provides series forecasting predictions useful "when your data has some kind of periodic component where events have a causal relationship and they happen (or miss to happen) in some point of time."
  • An internal update to TensorFlow, now using version 1.13.1 (formerly 1.12.0)
  • Assorted bug fixes

All of the above and more are detailed in the release notes.

The Model Builder components also received several updates, including: a new issue classification template (for classifying tabular data into many classes); improved evaluate and code generation steps; and fixes for customer feedback issues concerning installation errors, usability and stability.

About the Author

David Ramel is an editor and writer for Converge360.

comments powered by Disqus


  • Black White Wave IMage

    New Azure AI VMs Immediately Claim Top500 Supercomputer Rankings

    Visual Studio coders who dabble in artificial intelligence projects can now take advantage of new Azure virtual machines (VMs) featuring 80 GB NVIDIA GPUs that immediately claimed four spots on the TOP500 supercomputers list, Microsoft said.

  • Colorful Night IMage

    Auto Completions Speed Up in Java on Visual Studio Code

    Java jockeys using Microsoft's Visual Studio Code editor will see faster code completions thanks to a new language server.

  • New Toolkit for Writing Visual Studio Extensions (And Where to Find Extensions)

    Microsoft details a new Extensibility Essentials toolkit for VS 2022 and explains where to find your favorite tools.

  • New TypeScript 4.5 Improves Asynchronous Programming

    TypeScript 4.5 has shipped with a new Awaited type and Promise improvements for enhancing asynchronous programming in Microsoft's popular take on JavaScript that adds statically checked types.

Upcoming Events