genann

> I am very much a beginner in the space of machine learning While the (precious and useful) advice around seem to cover mostly the bigger infrastructures, please note that you can effectively do an important slice of machine learning work (study, personal research) with just a battery-efficiency-level CPU (not GPU), in the order of minutes, on a battery. That comes before going to "Big Data". And there are lightweight tools: I am current enamoured with Genann («minimal, well-tested open-source library implementing feedfordward artificial neural networks (ANN) in C», by Lewis Van Winkle), a single C file of 400 lines compiling to a 40kb object, yet well sufficient to solve a number of the problems you may meet. https://codeplea.com/genann // https://github.com/codeplea/genann After all, is it a good idea to use tools that automate process

I've been working on a deep learning library in C, and have been thinking about optimizing it for embedded applications specifically. https://github.com/siekmanj/sieknet Other than that, I'm not sure if there are many libraries for machine learning on microcontrollers. Genann comes to mind: https://github.com/codeplea/genann

genann is also a similar small neural network library written in C. https://github.com/codeplea/genann

This is cool. The documentation is very entertaining, although not something you'd show to your boss. Looks like it implements a lot more than just neural networks. Shameless plug: For a minimal neural network implementation in ANSI C, check out: https://github.com/codeplea/genann Sometimes lack of features is a feature.