Adam Optimizer Explained in Detail with Animations | Optimizers in Deep Learning Part 5
Adaptive Moment Estimation is an algorithm for optimization technique for gradient descent. The method is really efficient when working with large problems involving a lot of data or parameters. It requires less memory and is efficient. Intuitively, it is a combination of the ‘gradient descent with momentum’ algorithm and the ‘RMSP’ algorithm.
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⌚Time Stamps⌚
00:00 - Intro
00:40 - What is Adaptive Moment Estimation? ADAM
05:45 - Math behind ADAM
11:24 - The Verdict
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