A straightforward guide to building a perceptron system that learns to perform basic logical operations such as AND and OR.
You'll build a tiny but complete learning machine: a single perceptron packaged as a reusable Rust crate with training, prediction, and example binaries. The model learns the AND and OR logic gates and reveals its limits on XOR, giving you a clear view of how simple decision-makers behave.
You'll use the rand crate for realistic initialization and run examples like cargo run --example and to watch the perceptron improve in real time.
Build a configurable perceptron in Rust
Initialize weights and bias with rand
Compute predictions with a step activation
Train with epochs and learning rate
Evaluate on AND, OR, XOR tasks
Implement early stopping using tolerance
Basic Rust programming knowledge
Rust and cargo installed
Basic command-line experience
Understanding of binary classification
Comfort with arrays and slices
Configurable Perceptron Weights
Perceptron Training Logic
Prediction Method
Training Logic Gates
Training Logical OR
Perceptron Limits with XOR
