Machine Learning in C# with ML.NET

What You'll Learn

• Understand when to use ML.NET vs generative AI
• Build classification and regression pipelines in C#
• Train, evaluate, and deploy ML.NET models
• Import and run ONNX models in .NET applications
• Combine ML.NET predictions with Semantic Kernel agents

Prerequisites

• C# fundamentals
• .NET 8+ development environment

Learning Path Articles

1. 1

   What Is ML.NET? Machine Learning in C# for .NET Developers

   Understand ML.NET in plain terms: what it is, when to use machine learning in C#, and how it compares with Azure OpenAI and Semantic Kernel.

   Beginner 11 min read university
2. 2

   ML.NET Sentiment Analysis in C#: Predictive Analytics Tutorial

   Build a predictive analytics workflow with ML.NET in C#: train a sentiment model, evaluate metrics, and serve predictions from an ASP.NET Core API.

   Beginner 13 min read workshop
3. 3

   Run ONNX Models in .NET: HuggingFace Embeddings & Phi-3 Without Azure

   Run HuggingFace embedding models and Phi-3 locally in .NET with ONNX Runtime. No cloud APIs, no inference costs — pure C# offline AI inference.

   Intermediate 11 min read university