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| author | TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com> | 2024-04-29 22:06:12 -0400 |
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| committer | TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com> | 2024-04-29 22:06:12 -0400 |
| commit | 4d53fa14ee0cd615444aca6f6ba176e0ccc1b5be (patch) | |
| tree | 4d9f0527d9e6db4f92736ead0aa9bb3f840a0f89 /SI/Resource/Data Science/Machine Learning/Contents/Gradient descent.md | |
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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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