From digital assistants to home entertainment systems, there’s an explosion of interest in deploying deep-learning-enabled applications on embedded platforms.
Arm NN provides an easy way to deploy machine learning on power-efficient devices, bridging the gap between existing machine learning frameworks and the underlying hardware. It enables translation of existing frameworks – such as TensorFlow and Caffe – allowing them to run efficiently, without modification, across a variety of Arm Cortex CPUs and Arm Mali GPUs.
During this webinar, you will learn:
• How to get up and running with Arm NN on Linux
• How to use Streamline, Arm’s profiling tool, to analyze application performance