Making a practical machine learning project, end-to-end #MLmonday #ML #MachineLearning #Gaming
Jeremy’s blog posts the process of developing and implementing a practical machine learning (ML) project.
The goal of this project was to make a system that could play the card game Quiddler alongside human players. The reason for doing it was to have a vehicle to learn new technology. Therefore, to make this challenging I wanted a cloud hosted system to read the physical cards from a camera and deduce the best play.
When you visit this web page you can open the webcam and then take a photo of the cards in your hand and the card on the deck. Provide the number of cards in your hand as a hint and then ask for the best play. The screenshot shows that the cards have been recognised successfully and the suggested play is to pick up the deck card “o” and drop the “a”, then make the words “xenon” and “udo” for a score of 37.
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Python for Microcontrollers – Adafruit Daily — Python on Microcontrollers Newsletter: CircuitPython 2025 Wraps, Focus on Using Python, Open Source and More! #CircuitPython #Python #micropython @ThePSF @Raspberry_Pi
EYE on NPI – Adafruit Daily — EYE on NPI Maxim’s Himalaya uSLIC Step-Down Power Module #EyeOnNPI @maximintegrated @digikey