aprogrammer/dotnet-docs: This repository contains .NET Documentation.

docs/machine-learning/toc.yml
131 строка5 KB
Luis Quintanilla
Add Model Builder GPU instructions (#19559)
19 авг 2020, 02:30
19 авг 2020, 02:30fb6dfc8
- name: ML.NET
  href: index.yml
- name: Overview
  expanded: true
  items:
  - name: Model Builder & CLI
    items:
    - name: The ML.NET Model Builder tool
      href: automate-training-with-model-builder.md
    - name: The ML.NET Command-Line interface
      href: automate-training-with-cli.md
  - name: API
    items:
    - name: The ML.NET API
      href: how-does-mldotnet-work.md
- name: Tutorials
  items:
  - name: Model Builder & CLI
    items:
    - name: Predict prices (Model Builder & regression)
      href: tutorials/predict-prices-with-model-builder.md
    - name: Analyze sentiment using the ML.NET CLI
      href: tutorials/sentiment-analysis-cli.md
    - name: Analyze sentiment in Razor Pages (Model Builder & binary classification)
      href: tutorials/sentiment-analysis-model-builder.md
    - name: Categorize health violations (Model Builder & multiclass classification)
      href: tutorials/health-violation-classification-model-builder.md
  - name: API
    items:
    - name: Overview
      href: tutorials/index.md
    - name: Analyze sentiment (binary classification)
      href: tutorials/sentiment-analysis.md
    - name: Categorize support issues (multiclass classification)
      href: tutorials/github-issue-classification.md
    - name: Predict prices (regression)
      href: tutorials/predict-prices.md
    - name: Categorize iris flowers (k-means clustering)
      href: tutorials/iris-clustering.md
    - name: Recommend movies (matrix factorization)
      href: tutorials/movie-recommendation.md
    - name: Image Classification (transfer learning)
      href: tutorials/image-classification-api-transfer-learning.md      
    - name: Classify images (model composition)
      href: tutorials/image-classification.md
    - name: Forecast bike rental demand (time series)
      href: tutorials/time-series-demand-forecasting.md
    - name: Product Sales Analysis (anomaly detection)
      href: tutorials/sales-anomaly-detection.md
    - name: Detect objects in images (object detection)
      href: tutorials/object-detection-onnx.md
    - name: Classify sentiment using TensorFlow (text classification)
      href: tutorials/text-classification-tf.md
  - name: Infer.NET
    items:
    - name: Probabilistic programming with Infer.NET
      href: how-to-guides/matchup-app-infer-net.md
- name: Concepts
  items:
  - name: ML.NET tasks
    href: resources/tasks.md
  - name: Algorithms
    href: how-to-choose-an-ml-net-algorithm.md
  - name: Data transforms
    href: resources/transforms.md
  - name: Model evaluation metrics
    href: resources/metrics.md
  - name: Improve model accuracy
    href: resources/improve-machine-learning-model-ml-net.md
- name: How-to guides
  items:
  - name: Model Builder & CLI
    items:
    - name: Load data into Model Builder
      href: how-to-guides/load-data-model-builder.md
    - name: Install Model Builder
      href: how-to-guides/install-model-builder.md
    - name: Install GPU in Model Builder
      href: how-to-guides/install-gpu-model-builder.md
    - name: Install the CLI
      href: how-to-guides/install-ml-net-cli.md
    - name: Use the automated ML API
      href: how-to-guides/how-to-use-the-automl-api.md
  - name: API
    items:
    - name: Install extra dependencies
      href: how-to-guides/install-extra-dependencies.md
    - name: Load data
      href: how-to-guides/load-data-ml-net.md
    - name: Prepare data
      href: how-to-guides/prepare-data-ml-net.md
    - name: Train, evaluate, and explain the model
      items:
      - name: Train and evaluate a model
        href: how-to-guides/train-machine-learning-model-ml-net.md
      - name: Train a model using cross-validation
        href: how-to-guides/train-machine-learning-model-cross-validation-ml-net.md
      - name: Inspect intermediate pipeline data values
        href: how-to-guides/inspect-intermediate-data-ml-net.md
      - name: Determine model feature importance with PFI
        href: how-to-guides/explain-machine-learning-model-permutation-feature-importance-ml-net.md
    - name: Use the trained model
      items:
      - name: Save and load a model
        href: how-to-guides/save-load-machine-learning-models-ml-net.md
      - name: Use a model to make predictions
        href: how-to-guides/machine-learning-model-predictions-ml-net.md
      - name: Re-train a model
        href: how-to-guides/retrain-model-ml-net.md
      - name: Deploy a model to Azure Functions
        href: how-to-guides/serve-model-serverless-azure-functions-ml-net.md
      - name: Deploy a model to a web API
        href: how-to-guides/serve-model-web-api-ml-net.md
- name: Reference
  items:
  - name: ML.NET API Reference
    href: https://docs.microsoft.com/dotnet/api/?view=ml-dotnet
  - name: ML.NET API Preview API Reference
    href: https://docs.microsoft.com/dotnet/api/?view=ml-dotnet-preview
  - name: CLI reference
    href: reference/ml-net-cli-reference.md
- name: Resources
  items:
  - name: Overview
    href: resources/index.md
  - name: Glossary
    href: resources/glossary.md
  - name: Azure training resources
    href: resources/azure-training-concepts-model-builder.md
  - name: CLI telemetry
    href: resources/ml-net-cli-telemetry.md