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Backpropagation Playground
Watch the math unfold step by step. Forward pass computes the prediction, backward pass computes the blame, weight update fixes the mistake.
2-input → 3-hidden (sigmoid) → 1-output | Input: [1, 0.5] | Target: 1 | LR: 0.5
Press Step or Auto-Play to begin
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Weight Table
| Weight | Value |
|---|---|
| w₁₁ | 0.1500 |
| w₁₂ | 0.2000 |
| b₁ | 0.3500 |
| w₂₁ | 0.2500 |
| w₂₂ | 0.3000 |
| b₂ | 0.3500 |
| w₃₁ | 0.1000 |
| w₃₂ | 0.1500 |
| b₃ | 0.3000 |
| w₄₁ | 0.4000 |
| w₄₂ | 0.4500 |
| w₄₃ | 0.5000 |
| b₄ | 0.6000 |
Forward Pass
Backward Pass
Weight Update
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All computation runs in your browser using plain JavaScript math. No frameworks, no GPU — just the raw forward pass, chain rule, and gradient descent that powers every neural network.