When training neural networks to recognise things, what you need is a big pile of training data. You then need a subsequent pile of testing data to verify that the network is working as you’d expect.

Modern retrocomputing tricks often push old hardware and systems further than any of the back-in-the-day developers could have ever dreamed. How about a neural network on an original Mac? [KenDesigns] ...

An experimental computing system physically modeled after the biological brain "learned" to identify handwritten numbers with an overall accuracy of 93.4%. The key innovation in the experiment was a ...

Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...