Inspired by unixpickle's WeakAI Hopfield demo, this project implements a simple Hopfield Network for pattern recognition, using a custom grid-based interface for both training and testing. It demonstrates how a neural network can be trained to recall stored patterns from partial or noisy inputs. The implementation uses a grid-based visual representation for both input and output patterns. Additionally, all calculations are shown in matrix form to help visualize how the network operates.
Available here
