In addition to powerful deep learning frameworks like TensorFlow for Arduino, there are also classical ML approaches suitable for smaller data sets on embedded devices that are useful and easy to understand — one of the simplest is KNN.
One advantage of KNN is once the Arduino has some example data it is instantly ready to classify! We’ve released a new Arduino library so you can include KNN in your sketches quickly and easily, with no off-device training or additional tools required.
In this article, we’ll take a look at KNN using the color classifier example. We’ve shown the same application with deep learning before — KNN is a faster and lighter weight approach by comparison, but won’t scale as well to larger more complex datasets.