index.yml

### 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.service: dotnet-ml
  ms.topic: landing-page
  ms.collection: collection
  author: natke
  ms.author: nakersha
  ms.date: 04/15/2024

# 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: Overview of ML.NET
            url: overview.md
          - text: What is the ML.NET API?
            url: mldotnet-api.md
          - text: What is Model Builder?
            url: automate-training-with-model-builder.md
      - linkListType: video
        links:
          - text: Machine learning basics
            url: /shows/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
      - linkListType: get-started
        links:
          - text: ML.NET on Q&A
            url: /answers/topics/dotnet-mlnet.html

  # Get started
  - title: Get started in 10 minutes
    linkLists:
      - linkListType: quickstart
        links:
          - text: Get started with the ML.NET API (code-first)
            url: https://dotnet.microsoft.com/learn/ml-dotnet/get-started-tutorial/intro
          - text: Set up Model Builder in Visual Studio (low-code)
            url: how-to-guides/install-model-builder.md
          - text: Install the CLI on macOS, Windows, or Linux (low-code)
            url: how-to-guides/install-ml-net-cli.md

  # Tutorials - scenarios
  - title: Tutorials
    linkLists:
      - linkListType: learn
        links:
          - text: Predictive maintenance (Model Builder)
            url: /training/modules/predictive-maintenance-model-builder/
      - 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: Use object detection to recognize traffic signs (Model Builder)
            url: tutorials/object-detection-model-builder.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: ../../api/index.md?view=ml-dotnet&preserve-view=true
          - text: ML.NET CLI reference
            url: reference/ml-net-cli-reference.md
          - text: ML.NET samples
            url: https://github.com/dotnet/machinelearning-samples