As AI and Machine Learning continue to create business value for enterprises, the proliferation of machine learning to the edge is driving the next set of use cases. The ability to run ML models with low latency on the edge such as mobile devices and IoT devices allows for many new use cases to come to fruition.

In this video you will learn more about how our team has taken TensorFlow based models and used TFLite to deploy the model within an Android App. With this architecture, you can now use computer vision and image recognition right on the mobile device even in offline mode.

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