Machine learning features help you to handle machine learning frameworks, like TensorFlow and TensorFlow-Lite, with the construction of a data pipeline.
You can use the following machine learning features in your native applications:
You can create data pipelines that contain the machine learning model filters. The pipeline can be assembled and controlled with various elements of GStreamer.
You can construct, control, and train a machine learning model on-the-fly. The training can be done using the code or with a set of format that describes the model. These models can be trained on the device locally when needed.
You can register and deploy specific AI operations as an ML service and let other applications use this service via the network.
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