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Custom Vision ONNX in ML.NET (#29093)
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--- | ||
title: ML.NET tutorials | ||
description: Explore the ML.NET tutorials to learn how to build custom AI solutions and integrate them into your .NET applications. | ||
ms.date: 07/08/2019 | ||
ms.date: 05/18/2024 | ||
--- | ||
# ML.NET tutorials | ||
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The following tutorials enable you to understand how to use [ML.NET](../index.yml) to build custom machine learning solutions and integrate them into your .NET applications: | ||
The following tutorials help you understand how to use [ML.NET](../index.yml) to build custom machine learning solutions and integrate them into your .NET applications: | ||
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- [Sentiment analysis](sentiment-analysis.md): demonstrates how to apply a **binary classification** task using ML.NET. | ||
- [GitHub issue classification](github-issue-classification.md): demonstrates how to apply a **multiclass classification** task using ML.NET. | ||
- [Price predictor](predict-prices.md): demonstrates how to apply a **regression** task using ML.NET. | ||
- [Iris clustering](iris-clustering.md): demonstrates how to apply a **clustering** task using ML.NET. | ||
- [Recommendation](movie-recommendation.md): generate movie **recommendations** based on previous user ratings | ||
- [Image classification](image-classification.md): demonstrates how to retrain an existing TensorFlow model to create a custom image classifier using ML.NET. | ||
- [Anomaly detection](sales-anomaly-detection.md): demonstrates how to build an anomaly detection application for product sales data analysis. | ||
- [Detect objects in images](object-detection-onnx.md): demonstrates how to detect objects in images using a pre-trained ONNX model. | ||
- [Classify sentiment of movie reviews](text-classification-tf.md): learn to load a pre-trained TensorFlow model to classify the sentiment of movie reviews. | ||
- [Sentiment analysis](sentiment-analysis.md): Apply a **binary classification** task using ML.NET. | ||
- [GitHub issue classification](github-issue-classification.md): Apply a **multiclass classification** task using ML.NET. | ||
- [Price predictor](predict-prices.md): Apply a **regression** task using ML.NET. | ||
- [Iris clustering](iris-clustering.md): Apply a **clustering** task using ML.NET. | ||
- [Recommendation](movie-recommendation.md): Generate movie **recommendations** based on previous user ratings | ||
- [Image classification](image-classification.md): Retrain an existing TensorFlow model to create a custom image classifier using ML.NET. | ||
- [Anomaly detection](sales-anomaly-detection.md): Build an anomaly detection application for product sales data analysis. | ||
- [Detect objects in images](object-detection-onnx.md): Detect objects in images using a pre-trained ONNX model. | ||
- [Categorize an image from Custom Vision ONNX model](object-detection-custom-vision-onnx.md): Detect objects in images using an ONNX model trained in the Microsoft Custom Vision service. | ||
- [Classify sentiment of movie reviews](text-classification-tf.md): Load a pretrained TensorFlow model to classify the sentiment of movie reviews. | ||
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## Next Steps | ||
## Next steps | ||
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For more examples that use ML.NET, check out the [dotnet/machinelearning-samples](https://github.com/dotnet/machinelearning-samples) GitHub repository. | ||
For more examples that use ML.NET, see the [dotnet/machinelearning-samples](https://github.com/dotnet/machinelearning-samples) GitHub repository. |
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