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ML.NET documentation

Learn how to use open-source ML.NET to build custom machine learning models and integrate them into apps. Tutorials, code examples, and more show you how.

ML.NET basics

Overview

  • Overview of ML.NET
  • What is the ML.NET API?
  • What is Model Builder?

video

  • Machine learning basics

Concept

  • Machine learning tasks & algorithms
  • How to choose an algorithm

Get started

  • ML.NET on Q&A

Get started in 10 minutes

Quickstart

  • Get started with the ML.NET API (code-first)
  • Set up Model Builder in Visual Studio (low-code)
  • Install the CLI on macOS, Windows, or Linux (low-code)

Tutorials

Training

  • Predictive maintenance (Model Builder)

Tutorial

  • Analyze website comment sentiment (Model Builder)
  • Predict prices (Model Builder)
  • Categorize health violations (Model Builder & SQL Server)
  • Categorize support issues (API)
  • Classify images with Image Classification API (API)
  • Use object detection to recognize traffic signs (Model Builder)
  • Detect objects in images (API)
  • Detect anomalies in product sales (API)
  • Forecast bike rental demand (API & SQL Server)
  • Build a movie recommender (API)

How-to guides

How-To Guide

  • Load data from various sources
  • Prepare data for building a model
  • Train & evaluate a model
  • Make predictions with a trained model
  • Save & load a trained model
  • Retrain a model

Reference

Reference

  • ML.NET API reference
  • ML.NET CLI reference
  • ML.NET samples
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Your Privacy Choices
  • Previous Versions
  • Blog
  • Contribute
  • Privacy
  • Terms of Use
  • Trademarks
  • © Microsoft 2025