New: Build Neural Network With Ms Excel
This is where the magic happens. Standard Excel doesn't "learn" automatically; we must calculate the gradients (how much to change the weights) using formulas.
The gradient for the output layer is: (Prediction - Target) * Sigmoid_Primitive
Sigmoid derivative = Sigmoid * (1 - Sigmoid) build neural network with ms excel new
In cell M6:
=(I6# - K6) * (I6# * (1 - I6#)) This is where the magic happens
┌─────────────────────────────────────────────┐
│ Neural Network Builder [X] [?] │
├─────────────────────────────────────────────┤
│ Layers: │
│ [Layer 1: Input ] size: 5 │
│ [Layer 2: Hidden] size: 12 Act: ReLU [X]│
│ [Layer 3: Hidden] size: 6 Act: ReLU [X]│
│ [Layer 4: Output] size: 1 Act: Sigmoid │
│ [+ Add Layer] │
├─────────────────────────────────────────────┤
│ Training: │
│ Learning rate: [0.01 ▼] Epochs: [2000] │
│ Batch size: [32 ▼] Optimizer: [Adam ▼]│
│ Loss function: [Binary Cross-Entropy ▼] │
│ [ Initialize ] [ Train ] [ Predict ] │
├─────────────────────────────────────────────┤
│ Current Loss: 0.237 │ Loss chart (live) │
│ Best Loss: 0.191 │ \_/‾‾‾‾‾\_ │
└─────────────────────────────────────────────┘
