By following these steps, you have successfully created a functional neural network in Excel. While this approach is not scalable for deep learning or big data, it is an invaluable educational exercise for understanding: How neural network affect outputs. The role of activation functions (Sigmoid). How gradient descent works to minimize error.
The Mean Squared Error will drop from ~0.25 to <0.005. build neural network with ms excel full
Gradients for W2 (two entries): dLoss_dW2_1 (N10): = M10 * E10 // gradient wrt W2_1 dLoss_dW2_2 (O10): = M10 * G10 // gradient wrt W2_2 dLoss_db2 (P10): = M10 By following these steps, you have successfully created
| X1 | X2 | Y | | --- | --- | --- | | 0.5 | 0.2 | 0.7 | | 0.3 | 0.6 | 0.9 | | 0.8 | 0.1 | 0.4 | How gradient descent works to minimize error