This week (coinciding with Microsoft Ignite 2019) we announced the release of ML.NET 1.4 GA.
There are many new features such as:
New Deep Learning Image Classifier (GA): GPU support for training and inference Image Classifier ML models.
Database Loader (GA): You can train your model with data directly from any relational database supported by System.Data.
Enhanced for .NET Core 3.0 (GA): Performance improvements thanks to hardware intrinsics feature in .NET Core 3.0.
PredictionEnginePool for scalable deployments (GA): Recommended approach for multi-threaded scalable apps such as ASP.NET Core apps/services and Azure Functions
ML.NET and .NET support in Jupyter notebooks: You can now run any .NET code (C# / F#) in Jupyter notebooks and therefore run ML.NET code in it as well. Great for exploring and documenting model training experiments, data distribution exploration, data cleaning, plotting data charts, learning scenarios such as ML.NET courses, hands-on-labs and quizzes, etc.
This week (coinciding with Microsoft Ignite 2019) we announced the release of ML.NET 1.4 GA. There are many new features such as:
New Deep Learning Image Classifier (GA): GPU support for training and inference Image Classifier ML models.
Database Loader (GA): You can train your model with data directly from any relational database supported by System.Data.
Enhanced for .NET Core 3.0 (GA): Performance improvements thanks to hardware intrinsics feature in .NET Core 3.0.
PredictionEnginePool for scalable deployments (GA): Recommended approach for multi-threaded scalable apps such as ASP.NET Core apps/services and Azure Functions
ML.NET and .NET support in Jupyter notebooks: You can now run any .NET code (C# / F#) in Jupyter notebooks and therefore run ML.NET code in it as well. Great for exploring and documenting model training experiments, data distribution exploration, data cleaning, plotting data charts, learning scenarios such as ML.NET courses, hands-on-labs and quizzes, etc.
See details in the following Blog Posts:
Announcing ML.NET 1.4 general availability (Machine Learning for .NET)
Using ML.NET in Jupyter notebooks
.NET Core with Jupyter Notebooks