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Fix small typo in documentation link (#291)
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README.md

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@@ -42,7 +42,7 @@ These generic examples show how to use various models and input feeds with Windo
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- **[MNIST\UWP\cppcx](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/MNIST/UWP)**: a UWP C++/CX app that uses the MNIST model to detect numberic characters.
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- **[CustomTensorization](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/CustomTensorization)**: a Windows Console Application (C++/WinRT) that shows how to do custom tensorization.
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- **[Emoji8](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/Emoji8)**: a UWP C# app that uses the FER Emotion model to evaluate how well the user's facial expressions match randomly selected emojis.
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- **[CustomOperatorCPU](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/CustomOperatorCPU)**: a desktop app that defines multiple custom cpu operators. One of these is a debug operator which we invite you to integrate into your own workflow.
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- **[CustomOperatorCPU](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/CustomOperator)**: a desktop app that defines multiple custom cpu operators. One of these is a debug operator which we invite you to integrate into your own workflow.
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- **[AdapterSelection](https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/AdapterSelection)**: a desktop app that demonstrates how to choose a specific device adapter for running your model
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- **[PlaneIdentifier](https://github.com/Microsoft/Windows-AppConsult-Samples-UWP/tree/master/PlaneIdentifier)**: a UWP app and a WPF app packaged with the Desktop Bridge, sharing the same model trained using [Azure Custom Vision service](https://customvision.ai/). For step-by-step instructions for this sample, please see the blog post [Upgrade your WinML application to the latest bits](https://blogs.msdn.microsoft.com/appconsult/2018/11/06/upgrade-your-winml-application-to-the-latest-bits/).
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