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### YamlMime:Landing
title: ML.NET Documentation
summary: 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.
metadata:
title: ML.NET Documentation - Tutorials, API Reference
description: 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.
ms.prod: dotnet-ml
ms.topic: landing-page
ms.collection: collection
author: natke
ms.author: nakersha
ms.date: 10/30/2019
# linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
landingContent:
# Basics
- title: ML.NET Basics
linkLists:
- linkListType: overview
links:
- text: What is ML.NET?
url: how-does-mldotnet-work.md
- linkListType: video
links:
- text: Machine learning basics
url: https://channel9.msdn.com/Series/MLNET/MLNET-Machine-Learning-Introduction-1-of-8
- linkListType: concept
links:
- text: Machine learning tasks & algorithms
url: resources/tasks.md
- text: How to choose an algorithm
url: how-to-choose-an-ml-net-algorithm.md
# Get started
- title: Get started in 10 minutes
linkLists:
- linkListType: quickstart
links:
- text: Set up Model Builder in Visual Studio
url: how-to-guides/install-model-builder.md
- text: Get started with the ML.NET API
url: https://dotnet.microsoft.com/learn/ml-dotnet/get-started-tutorial/intro
- text: Install the CLI on Mac OS, Windows, or Linux
url: how-to-guides/install-ml-net-cli.md
# Tutorials - scenarios
- title: Tutorials
linkLists:
- linkListType: tutorial
links:
- text: Analyze website comment sentiment (Model Builder)
url: tutorials/sentiment-analysis-model-builder.md
- text: Predict prices (Model Builder)
url: tutorials/predict-prices-with-model-builder.md
- text: Categorize health violations (Model Builder & SQL Server)
url: tutorials/health-violation-classification-model-builder.md
- text: Categorize support issues (API)
url: tutorials/github-issue-classification.md
- text: Classify images with Image Classification API (API)
url: tutorials/image-classification-api-transfer-learning.md
- text: Classify images using model composition (API)
url: tutorials/image-classification.md
- text: Detect objects in images (API)
url: tutorials/object-detection-onnx.md
- text: Detect anomalies in product sales (API)
url: tutorials/sales-anomaly-detection.md
- text: Forecast bike rental demand (API & SQL Server)
url: tutorials/time-series-demand-forecasting.md
- text: Build a movie recommender (API)
url: tutorials/movie-recommendation.md
# API Card
- title: How-to guides
linkLists:
- linkListType: how-to-guide
links:
- text: Load data from various sources
url: how-to-guides/load-data-ml-net.md
- text: Prepare data for building a model
url: how-to-guides/prepare-data-ml-net.md
- text: Train & evaluate a model
url: how-to-guides/train-machine-learning-model-ml-net.md
- text: Make predictions with a trained model
url: how-to-guides/machine-learning-model-predictions-ml-net.md
- text: Save & load a trained model
url: how-to-guides/save-load-machine-learning-models-ml-net.md
- text: Retrain a model
url: how-to-guides/retrain-model-ml-net.md
# API Card
- title: Reference
linkLists:
- linkListType: reference
links:
- text: ML.NET API reference
url: https://docs.microsoft.com/dotnet/api/?view=ml-dotnet
- text: ML.NET samples
url: https://github.com/dotnet/machinelearning-samples
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