ML.NET Model Builder Update Boosts Image Classification -- Visual Studio Magazine

ML.NET Model Builder Update Boosts Image Classification

By David Ramel
11/13/2019

Microsoft announced an update to the Model Builder component of its ML.NET machine learning framework, boosting image classification and adding "try your model" functionality for predictions with sample input.

Model Builder is the Visual Studio UI tooling that .NET developers use to work with the ML.NET cross-platform machine learning framework, which hit version 1.0 in May. "Developers with no ML expertise can use this simple visual interface to connect to their data stored in files or SQL Server, train the model and generate code for model training and consumption," Microsoft says. The ML.NET framework also works with a CLI (command-line interface) for use outside of the Visual Studio IDE, and AutoML, Automated Machine Learning, the Microsoft Research project used to automate the process of building custom models.

In an update post published yesterday (Nov. 12), program manager Bri Achtman announced the two new primary features:

Image classification scenario -- locally train image classification models with your own images: "We showed off this feature in .NET Conf to classify the weather in images as either sunny, cloudy, or rainy, and now you can locally train image classification models in Model Builder with your own images!" Note that image classification doesn't work with the ML.NET CLI.
Try your model -- make predictions on sample input data right in the UI: "After training a model in Model Builder, you can use the model to make predictions on sample input right in the UI for both text and image scenarios. For instance, for the dog vs. cat image classification example, you could input an image and see the results in the Evaluate step of Model Builder."

In addition to image classification, ML.NET is used for sentiment analysis, customer segmentation, sales spike detection, product recommendation, object detection and several other machine learning scenarios. Its Model Builder development is carried out on GitHub, and Model Builder is available on the Visual Studio Marketplace -- or it can be installed via the Visual Studio Extensions menu.

Model Builder (still in preview) has been installed more than 54,000 times, according to its marketplace entry, earning a 4.6 (0-5 scale) from 19 developers who reviewed it.

About the Author

David Ramel is an editor and writer at Converge 360.

Printable Format

comments powered by Disqus

Featured

Compare New GitHub Copilot Free Plan for Visual Studio/VS Code to Paid Plans

The free plan restricts the number of completions, chat requests and access to AI models, being suitable for occasional users and small projects.
Diving Deep into .NET MAUI

Ever since someone figured out that fiddling bits results in source code, developers have sought one codebase for all types of apps on all platforms, with Microsoft's latest attempt to further that effort being .NET MAUI.
Copilot AI Boosts Abound in New VS Code v1.96

Microsoft improved on its new "Copilot Edit" functionality in the latest release of Visual Studio Code, v1.96, its open-source based code editor that has become the most popular in the world according to many surveys.
AdaBoost Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The implementation follows the original source research paper closely, so you can use it as a guide for customization for specific scenarios.
Versioning and Documenting ASP.NET Core Services

Building an API with ASP.NET Core is only half the job. If your API is going to live more than one release cycle, you're going to need to version it. If you have other people building clients for it, you're going to need to document it.