Technology Selection

by dotnet0608d8924cd3MIT5.5K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).

Instructions only
  1. 0608d8924cd3Currentcommit 0608d89Published Oct 8, 2026

Source and attribution

Source:dotnet/skillsinplugins/dotnet-ai/skills/technology-selectionat commit0608d89

License: MIT

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal