In this third workshop on TinyML, we go one step further with the audio event detection model and explore techniques for improving the model all the way to production quality. In particular, we will learn how to properly evaluate a model’s performance and how to achieve the highest possible accuracy while minimizing the latency and resource usage on a tiny device.
While standard ML workflows can get you quite far, optimizing your machine learning model to become production-ready requires some additional insight and effort. In this workshop, we will focus on three important aspects of model improvement:
In the practical part of the workshop, we will apply these techniques to our running audio event detection use case, but again you are welcome to work with your own case, and we will be happy to assist you the best we can.
This workshop will run in AU Herning in parallel via a video link
All workshops and dates
This is the third of 3 workshops, that is also organised and streamed to AU Herning. You can sign up for one of all three workshops here:
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