🧠 Neural Network Playground
Click on the grid to add data points. Watch the network learn to separate them.
📊 Decision Boundary — Click to add Red/Blue data points
Class A (Red)
Class B (Blue)
Network Prediction
🔗 Network Architecture — 2 Inputs → 3 Hidden → 1 Output
InputX₁, X₂
Hidden3 Neurons
OutputClass
H1
H2
H3
OUT
Epoch: 0
Loss:
—
Accuracy:
—
Data Points:
0
How it works: This is a real neural network with 2 inputs (X, Y coordinates), 3 hidden neurons, and 1 output. Click on the grid to add data points — 🔴 Red on one side, 🔵 Blue on the other. Then hit Auto Train and watch the purple decision boundary form as the network learns to separate the classes. The bars show how weights adjust. The neurons light up when activated. This is the same math powering image recognition, chatbots, and self-driving cars!
