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diff --git a/SI/Resource/Data Science/Machine Learning/Contents/Gradient descent.md b/SI/Resource/Data Science/Machine Learning/Contents/Gradient descent.md new file mode 100644 index 0000000..fdf8905 --- /dev/null +++ b/SI/Resource/Data Science/Machine Learning/Contents/Gradient descent.md @@ -0,0 +1,21 @@ +--- +id: 2023-12-17 +aliases: December 17, 2023 +tags: +- link-note +- Data-Science +- Machine-Learning +- Gradient-descent +--- + +# Gradient Descent + +- Update parameters that minimize values of loss functions +- **Instantaneous is always _0_** +- Therefore, update parameter that a derivative of loss function is equal to 0 + +## Pseudo Code + +1. Find the derivative of the loss function at the current parameters. +2. Update parameters in the opposite direction of the derivative +3. Repeat steps 1 and 2 as many epochs (hyperparameter) until the differential value becomes 0.
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