ML.NET Machine Learning Framework Updated
Microsoft's open source machine learning framework, ML.NET, has been updated to version 1.2, continuing to add features to help .NET developers use their familiar tools and languages to infuse ML functionality into their applications.
ML.NET includes components such as Model Builder (a Visual Studio UI tool), a CLI (command-line interface) and AutoML (Automated Machine Learning used to build custom models).
Having only hit v1.0 status in May, the framework continues to mature as Microsoft adds new features and functionality for its multiple use cases that include:
- Sentiment analysis
- Product recommendation
- Price prediction
- Customer segmentation
- Object detection
- Fraud detection
- Sales spike detection
- Image classification
- Sales forecasting
In a July 17 announcement post, Microsoft's Cesar De la Torre, program manager, said ML.NET 1.2 highlights include:
- General availability of TimeSeries support for forecasting and anomaly detection:
"Developers can use the Microsoft.ML.TimeSeries package for many scenarios such as: detecting spikes and changes in product sales using an anomaly detection model or creating sales forecasts which could be affected by seasonality and other time related context."
- General availability of ML.NET packages to use TensorFlow and ONNX models:
"ML.NET has been designed as an extensible platform so that you can consume other popular ML models such as TensorFlow and ONNX models and have access to even more machine learning and deep learning scenarios, like image classification, object detection, and more."
Easily integrate ML.NET models in web or serverless apps with Microsoft.Extensions.ML integration package (preview):
"This package makes it easier to integrate loading ML.NET model for scoring in ASP.NET apps, Azure Functions and web services. Specifically, the package allows a developer to use Microsoft.Extensions.ML for loading the ML.NET model using Dependency Injection, and optimizing the model’s execution and performance in multi-threaded environments such as ASP.NET Core apps."
- ML.NET CLI updated to 0.14 (preview):
"You can use the ML.NET CLI to automatically generate an ML.NET model and underlying C# code. You can run the ML.NET CLI on any command-prompt (Windows, Mac, or Linux)."
- Model Builder updates:
- Expanding support to .txt files and more delimiters for values
- No limits on training data size
- Smart defaults for training time for large datasets
- Improved model consumption experience
More information is available in the release notes for this backwards-compatible release.
David Ramel is the editor of Visual Studio Magazine.