An Xcode Playground to show how to build and train a Perceptron in Pure Swift
Shows how a trained perceptron makes predictions on new inputs. Features:
- Basic perceptron structure for making predictions
- Example inference calls with different input combinations
- Step-by-step calculation breakdown (dot product, weighted sum, activation)
- Comments showing working weights for an AND gate implementation
Demonstrates the complete perceptron training process with step-by-step visualization. Features:
- Implementation of the perceptron algorithm with weights and bias
- Training datasets for logical gates (AND, OR, XOR)
- Detailed training loop showing weight updates, error calculations, and convergence
- Real-time feedback showing how the perceptron learns from mistakes
- Final validation testing the trained model