This project has the goal of identifying the notes present in a given musical chord. The input sounds are given by the UMA database, which have been processed to produce matrices, assigning magnitudes to each one of the 88 notes in a piano. By deploying the network in Nengo, I was able to approach the problem from a different way most ML scientists have done, namely by utilising different representations of the data, and learning rules.