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