Optimizers in Deep Learning | Part 1 | Complete Deep Learning Course

This video breaks down the key algorithms that fine-tune neural network parameters for optimal performance. From classic techniques like Gradient Descent to advanced methods like Adam and RMSprop, explore how optimizers play a crucial role in training models effectively. Watch to gain insights into choosing the right optimizer for your deep learning tasks and enhancing model convergence.

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⌚Time Stamps⌚
00:00 - Intro
00:28 - Intro to Optimizers
02:33 - Role Of optimizers
08:00 -Types Of Optimizers
11:08 - The Challenges?
21:06 - What next?