Embedded machine learning projects are complex.
They are constrained by environmental factors, they require tradeoffs between accuracy and available hardware resources, and often need expert knowledge about the use case. To successfully develop an embedded machine learning solution, it will be necessary to choose the right tools and the right methods, and, combine them to perfection so that they produce the desired result.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/eon-tuner-search-space-and-custom-block-support