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A brief introduction to ANNs - part 1 ANNs (Artificial Neural Networks) are systems that can process information using connected components called neurons . ANNs are inspired by real (biological) neural networks like the brain. ANNs are widely used for real-world information processing tasks. In the image below (courtesy of Google Street View) you can see that car number plates have been blurred. Google hides them to protect privacy, and the software that recognises what to blur is a Neural Network. Image courtesy Google StreetView The software   As I said yesterday , I developed the software in APL on a Raspberry Pi. You’ll find instructions on how you can run it further down. Neurons An ANN is made up of neurons . Neurons are usually grouped into one or more layers. Many types of neuron have been proposed, but they all have certain characteristics in common. A neuron has one or more inputs and a single output. Associated with each input is a weight....

Neural Networks on the Raspberry Pi I've been having some fun experimenting with ANNs ( Artificial Neural Networks ) on the Raspberry Pi . I've been interested in ANN research for a very long while: I wrote my first simulator back in 1974. I developed that first version in ALGOL60. I've recently re-written and extended it in Dyalog APL , and now it runs on the Raspberry Pi. Why APL? I've found APL a great choice for ANN research and education, for several reasons: It's easy to learn, and fun! It's concise and easy to test. It handles arrays naturally. It has a rich set of primitives for data manipulation and calculation. It supports a pure functional programming style. Dyalog APL has great support for parallel computing. The Raspberry Pi version is free for non-commercial use. Inexpensive ANN computing I'm using a Raspberry Pi B model 3, but it runs acceptably fast on earlier versions of the Pi. I haven't yet tried it on the Pi ...