Machine learning on Raspberry Pi just took a big step forward

Raspberry Pi is a capable little machine, but if you're interested in developing your own embedded machine-learning applications, training custom models on the platform has historically been tricky due to the Pi's limited processing power. But things have just taken a big step forward. Yesterday, Edge Impulse, the cloud-based development platform for machine learning on edge devices, announced its foray into embedded Linux with full, official support for the Raspberry Pi 4. As a result, users can now upload data and train their own custom machine-learning algorithms in the cloud, and then deploy them back to their Raspberry Pi. SEE: C programming language: How it became the foundation for everything, and what's next (free PDF) (TechRepublic) Four new machine-learning software development kits (SDKs) for Raspberry Pi are available week, including C, Go, Node.js and Python, allowing users to program their own custom applications for inferencing. Support for object detection has also been added, meaning Raspberry Pi owners can use camera data captured on their device to train their own custom object detection algorithms, instead of having to rely on'stock' classification models.