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You are training a two‑layer neural network (2 inputs → 2 hidden neurons → 1 output neuron) to learn the XOR gate using sigmoid activation and Gradient Descent.
Forward Pass
Compute hidden layer pre‑activations
zhand activations
h.
Compute output pre‑activation
zoand prediction
y^.
Round each value to two decimals.
Error
Compute loss:
Round to two decimals.
Backward Pass (Chain Rule)
Compute output delta:
Compute hidden deltas:
Round all deltas to two decimals.
Weight Updates
Update output weights and bias:
Update hidden weights and biases:
Round all updated parameters to two decimals.