Artificial intelligence · University
One gradient-descent parameter update · formula reference
The gradient and learning rate belong to the specified loss and parameterization.
Formula
The gradient and learning rate belong to the specified loss and parameterization.
wnew = w − η∂L/∂w
Worked example
At w=-1, a loss gradient is -11. With learning rate 0.2, calculate one gradient-descent update to w. Round the final result to 4 decimal places if needed.
Subtract learning-rate times gradient: -1−(0.2)(-11).
1.2
Prerequisites and checking
Algebra and the topic definitions. Keep units and rounding consistent. State the model conditions before applying the formula.
Further reading and review references
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