EmojiIntelligence

Why we included this project

Most neural network tutorials hand you a framework and tell you to trust the math. EmojiIntelligence takes the opposite route: the network is written by hand in Swift, runs inside Apple's Playground, and learns to recognize hand-drawn emojis. Each sketch is downscaled to an 8x8 grid, so the model reads 64 binary pixels through fully-connected input, hidden, and output layers with a sigmoid activation. The README walks through weights, connections, and the activation function in plain language, which makes the whole pipeline from pixel encoding to classification easy to follow without a framework obscuring the steps. It is a teaching demo, not something you would deploy, but it is a genuinely clear way to see how a small network learns.