Neural Network Learning Simulator
Choose a Pattern to Learn:
Input Layer
Click pixels to draw
Hidden Layer
Feature Detector
Output Layer
OUT
Target Output: 0.5
Error Function
0.50
Goal: Get this as close to 0.00 as possible!
Input → Hidden Weights
Hidden Layer
Output Layer
How it works:
- Weights determine how much each input affects the next layer
- Biases shift the activation threshold of neurons
- Error measures how far your output is from the target
- Try to minimize the error by adjusting weights and biases!