When .NET meets machine learning

ML.NET is the open source cross-platform machine learning framework for .NET developers. You can use C# or F# to create custom ML models without leaving the .NET ecosystem. ML.NET enables you to add machine learning to .NET applications in online or offline scenarios. With this feature, machine learning applications use patterns in data to make predictions without the need for explicit programming.

ML.NET is the machine learning model , which specifies the steps required to transform input data into predictions. With ML.NET, you can train custom models by specifying algorithms, or import pre-trained TensorFlow and ONNX models. Once you have a model, you can add it to the application to make predictions. Examples of the types of predictions that can be made using ML.NET:

ML.NET runs on Windows, Linux and macOS using .NET Core or Windows using .NET Framework. All platforms support 64-bit. Windows supports 32-bit, except for TensorFlow, LightGBM and ONNX related functions.

After a brief introduction of what is ML.NET, we prepared for you machine learning articles Let's Learn .NET series of columns , to help you more intuitive understanding, and end of the text is also accompanied by free learning material , rich in content, You can collect it first and then learn it!