Observe Your Backyard Birds with a Custom ML Model @Raspberry_Pi #PiDay #RaspberryPi
from Jen Looper via hackster.io
Many developers are curious about using machine learning techniques in their apps. Digging into the processes involved, it becomes clear that you need to first define the problem that you’re trying to solve and ensure that you need a machine learning model in the first place. For many visual identification tasks, it’s obvious that machine learning (“ML”) is very helpful, as it allows a computer to “learn without being explicitly programmed”.
Rather than requiring a program to identify every bird by feeding an image of every existing creature into a database, we can use a technique of building a ML model which is an algorithm trained to recognize patterns and make ‘educated guesses’. Fed plenty of good quality images of cardinals, for example, a ML model would presume that the red bird at the feeder would most likely be a cardinal, and not a blue jay, based on patterns it has deduced in the images it has ‘seen’.
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