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If your dataset is on a different server, you can run the same notebook in the notebook server to download and extract the dataset, or you can download the dataset to your local computer using the pip install command.
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After the dataset has been downloaded and preprocessed, we now need to train the classifier. TAO includes built-in support for scikit-learn, which is a scikit-learn compatible implementation of a very popular machine learning toolkit. TAO currently offers a number of different classifiers, each with their own set of hyperparameters.
You can interact with the toolkit through the input APIs. You'll need to provide a context to the input system:
Either via a System.Windows.Interop.WindowsHolographicInterop object (for Microsoft HoloLens):
Or a System.Windows.Interop.WindowsMixedRealityInterop object (for Microsoft Mixed Reality headsets):
Holographic XAML Toolkit: The Holographic XAML Toolkit was a set of APIs that allowed you to render x86 apps in Holographic worlds. However, the developer surface was very limited and did not allow you to customize UI elements, so it is no longer supported.
Hosted Runtime: The Holographic Cloud Hosted Runtime for HoloLens was a compatibility layer that allowed Windows Store apps to run as Windows Holographic 2 apps. It provided a universal app runtime, but was limited to x86 apps. This layer is no longer supported and is no longer available.
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