Machine Learning for .NET developers

on YouTube ↗45m

" summary

Overview of a hands‑on .NET workflow that uses ML.NET and Visual Studio Model Builder to AutoML a regression for taxi fares from ~19,000 CSV rows, with default 5‑fold cross‑validation, reporting R² ≈ 0.93. The demo generates code that creates a model.zip, loads it into a PredictionEngine, and predicts live (example: actual $13 -> predicted $13.07). Shows pipeline steps (one‑hot encoding, feature concat, trainer selection), export, and easy app integration.

AI-written summary · about

" chapters (5)

1. 0:00Start
2. 3:33Al and ML in everyday life
3. 12:04Different ML tasks
4. 17:06Overfitting and underfitting
5. 23:07Getting started with Machine Learning can be hard

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