Creating a Multilayer Perceptron from Scratch

Last Updated on August 19, 2026 by Editorial Team Author(s): Caden Lippie Originally published on Towards AI. Creating a Multilayer Perceptron from Scratch A perceptron is a fundamental component of artificial neural networks. Inspired by the neurons in our brains*, these perceptrons make decisions and “learn” by iterating to minimize errors. When these single perceptrons are combined in layers, they form networks that can “learn” more complex patterns and make more nuanced decisions. *Organic neurons can have different purposes, and more neurons do not necessarily mean more intelligence. I think this is really interesting because this is very similar to how artificial neurons work.Fun Fact: The African elephant brain has 257 billion neurons, which is 3x the human brain. — https://pmc.ncbi.nlm.nih.gov/articles/PMC4053853/ In an attempt to grasp these mechanisms more thoroughly, I decided to create my own simple multilayer perceptron (MLP) and compute everything by hand (using a calculator). This process gave me a more confident and comprehensive understanding of this concept, which I can lean on when dealing with more complex systems. This process also helped to demystify AI and h…