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 Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do not change the destination, only the path. Each method adds a mechanism that fixes a limitation of the previous one, making the movement faster, more stable, or more adaptive. The goal stays the same. The update becomes smarter.
The post The Machine Learning “Advent Calendar” Bonus 2: Gradient Descent Variants in Excel appeared first on Towards Data Science. Read More  

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