machinelearning and mlnetacidemo
Project B demonstrates how to deploy models created with the machine learning framework in Project A using specific cloud and container technologies, making them complementary tools.
About machinelearning
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
Provides AutoML capabilities for automated model selection and hyperparameter tuning, plus native support for consuming pre-trained TensorFlow and ONNX models. Built on a modular pipeline architecture that handles data loading from files/databases, feature transformations, and algorithm composition—enabling scenarios like classification, regression, forecasting, and anomaly detection. Runs on .NET Core and .NET Framework across Windows, Linux, macOS, and ARM64 architectures.
About mlnetacidemo
lqdev/mlnetacidemo
Deploying .NET Machine Learning Models with ML.NET, ASP.NET Core, Docker and Azure Container Instances (ACI)
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work