Iteration
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Training Example
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Current Loss
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Current Phase
Idle
activation = sigmoid( Σ (input × weight) + bias )
Σ means "add all the weighted inputs together."
Current Example
Study Hours—
Sleep Hours—
→
Prediction—
vs
Actual—
Inside one learning step ?
Pause training, then click any hidden or output node in the diagram.
No node selected yet.
Before → After Update
Run a training step to see a weight and bias change.
Loss Before → After
Run a training step to compare loss before and after.
Try the Trained Network
This does not change any weights or biases — it only asks the network to make an estimate.
The ANN does not know the exact answer. It learns patterns from the examples and uses those patterns to make an estimate. With only five examples, predictions are rough estimates, not guaranteed facts.
Training summary — in simple words
Once you start training, this section will explain in plain language what the network learned and how.