Say I have an Machine/Deep learning algorithm I developed on a desktop pc to achieve a real-time classification of time series events from a sensor. Once the algorithm is trained and performs good, I want to implement it on an low power embbeded system, with the same sensor, to classify events in real-time:
- How can I know if the low power embedded system is fast enough to allow real-time classification regarding the algorithm (knowing it in advance would avoid to implement and try multiple architectures) ?
- Machine/Deep learning algorithm are usually developed in python. Is there easy ways to transfer the code from python to a more embeddable langage ?