Microsoft Machine Learning Kit for Lobe with Raspberry Pi 4 2GB

Machine learning is revolutionizing software development, yet it's been out of reach for most people. At Adafruit, we believe everyone should have access to this amazing technology. That's why we've partnered with Lobe to offer an easy - to - use machine learning kit at a discounted price. This kit has all the parts you need to turn your machine - learning ideas into reality. Note: While Lobe works well with the included 2GB Raspberry Pi 4, for the best performance, we suggest using a 4GB model. The kit includes the Adafruit BrainCraft HAT for Raspberry Pi 4, a 4GB RAM Raspberry Pi 4 Model B, an 8 - Megapixel Raspberry Pi Camera Board v2, a camera board case with tripod mount, an official power supply, a flex cable, and an 8GB SD card. We'll use the free and user - friendly Lobe app to create machine - learning models. Just show Lobe some examples of what you want it to learn, and it'll train a custom model for you. You can use this model directly on the Raspberry Pi or within the Lobe app. No soldering is needed. Just plug the parts together, and you can start your machine - learning adventure in less than an hour! The BrainCraft HAT is designed for edge machine learning. It features a 240×240 TFT IPS display for output, slots for camera cables, a 5 - way joystick, input buttons, left and right microphones, headphone and speaker outputs, three RGB DotStar LEDs, and STEMMA connectors. There's also a controllable mini - fan to keep your Pi cool during intense calculations, and an on/off switch to disable the audio codec. The STEMMA QT port allows you to connect heat image sensors, accelerometers, and other devices. Check out the Lobe GitHub repo at https://github.com/lobe/lobe - adafruit - kit.

Using this machine learning kit is a breeze. First, take all the parts out of the box. You don't need to solder anything. Just plug the components together as described. For creating machine - learning models, open the Lobe app. Show it examples of what you want it to learn, and it'll train a custom model for you. You can use this model on the Raspberry Pi or right inside the Lobe app. Remember, while the 2GB Raspberry Pi 4 included in the kit works with Lobe, for better performance, you might want to use a 4GB model. When using the BrainCraft HAT, be aware of the on/off switch for the audio codec. You can turn it off when you don't want it to listen. Also, the mini - fan at the bottom can be used to keep the Pi cool during heavy calculations. For maintenance, keep the components clean and dry. Don't expose them to extreme temperatures or humidity. If you want to expand the kit, use the STEMMA QT port to connect additional sensors or devices like heat image sensors or accelerometers.