ML.NET video tutorials (notes)

This is not a course. It is a pile of notes for videos I want to make before I get distracted by another library with Frank. in the name.

Facts: where ML.NET sits in the ecosystem

ML.NET is Microsoft’s .NET-first ML stack—data loading (IDataView), training pipelines, evaluation metrics, and deployment patterns documented under Microsoft Learn. ¹

Model Builder (Visual Studio extension) and the mlnet CLI automate common scenarios (classification, regression, recommendation, computer vision) so you can iterate without writing boilerplate trainers by hand. ²

ONNX interoperability matters because academic and industry workflows often train in Python then export; ML.NET documents the ONNX Runtime dependency and how to run ONNX models from .NET. ³

Ethics / optics: game-adjacent demos (aim bots, wall hacks as pedagogy) should foreground responsible disclosure—teach detection and adversarial robustness, not cheat distribution. Microsoft publishes Responsible AI principles and Azure Machine Learning documentation on fairness, interpretability, and human review—useful guardrails even for scratch tutorials. ^{4 5}

Concept

Most ML.NET content falls into two buckets:

1. “Data scientists, look — C# exists.”
2. “C# devs, you can be ML people too, here is a spreadsheet and a dream.”

Both are fine. Neither is what I want to build. I want messier, more playful stuff: things you can break, things that feel like games, things where “don’t try this in prod” is the whole point. Yes, that includes the morally questionable territory of aim-bot-shaped pedagogy — teaching, not cheating. Calm down.

Episode 0

Draft / scratch lives in the monorepo of chaos:

• Episode 0 (markdown) on GitHub

If that link rots, the internet deserved it.

References

• Microsoft Learn — ML.NET documentation hub
• Microsoft Learn — What is ML.NET?
• Microsoft Learn — Model Builder
• Microsoft Learn — ML.NET CLI
• Microsoft Learn — Install ONNX Runtime to use with ML.NET
• Microsoft Learn — Save and load a model in ML.NET (general persistence; ONNX loading is covered in ONNX-specific topics above)
• ONNX Runtime (GitHub)
• Microsoft — Responsible AI
• Microsoft Learn — Responsible machine learning (Azure ML)

1. Microsoft Learn — What is ML.NET? https://learn.microsoft.com/dotnet/machine-learning/how-does-mldotnet-work ↩

2. Microsoft Learn — What is Model Builder? https://learn.microsoft.com/dotnet/machine-learning/automate-training-with-model-builder ↩

3. Microsoft Learn — Install ONNX Runtime to use with ML.NET (ONNX Runtime packages and GPU/CPU notes). https://learn.microsoft.com/dotnet/machine-learning/how-to-guides/install-onnx-runtime ↩

4. Microsoft — Responsible AI overview (principles and practices). https://www.microsoft.com/ai/responsible-ai ↩

5. Microsoft Learn — What is responsible machine learning? (Azure Machine Learning). https://learn.microsoft.com/azure/machine-learning/concept-responsible-machine-learning ↩