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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Eink, E-paper, Think Ink – Collin shares six segments pondering the unusual low-power display technology that somehow still seems a bit sci-fi – http://adafruit.com/thinkink
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, TinyGO, or even use the Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for CircuitPython, MakeCode, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.