Accelerate Model Performance with Just 2 Lines of Code Using OpenVINO Integration with TensorFlow

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In our last webinar, we showed you how to get an Object Detection and Human Pose Estimation Demo running on your laptop with OpenVINO and Jupyter Notebooks (you can find that webinar here).

In this session, we will introduce you to OpenVINO integration with TensorFlow, which is designed to accelerate your TensorFlow workflow by just adding 2 additional lines of code. With this new integration, you will be able to accelerate over 270 TensorFlow models. Think of all the other innovative AI applications you will be able to create once you’re free from performance constraints. The limitations to what you can build will only be bound by your imagination.

Available now On-Demand:

Learning how to accelerate your TensorFlow workflow by adding just two lines of code
Learning about OpenVINO integration with TensorFlow and getting the complete list of over 270 TensorFlow models that you’ll be able to accelerate with two lines of code

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Accelerate Model Performance with Just 2 Lines of Code Using OpenVINO Integration with TensorFlow

Register to View On-Demand

Ethan Yang