Training deep neural networks like Transformers is challenging. They suffering from vanishing gradients, ineffective weight updates, and slow convergence. In this video, we break down one of the most powerful solutions: Residual Connections in Transformers

What you’ll learn in this video:

Why training deep networks is difficult?
How residual connections work and why they are game-changers
The key advantages of residual connections
How residual connections fit seamlessly into Transformers (inside the Add & Norm step)

By the end of this video, you’ll understand why residual connections in transformers stabilize its training and boost deep learning performance—especially in architectures like BERT and GPT!



Timestamps:
0:00 Intro
0:18 Problems in training a Deep Network
2:45 Residual Connections
5:05 Advantages & concerns of Residual Connections
8:20 Residual Connections in Transformers
10:14 Outro



Follow my entire Transformers playlist :

Transformers Playlist: https://www.youtube.com/watch?v=lRylkiFdUdk&list=PLuhqtP7jdD8CQTxwVsuiFYGvHtFpNhlR3&index=1&t=0s



RNN Playlist: https://www.youtube.com/watch?v=lWPkNkShNbo&list=PLuhqtP7jdD8ARBnzj8SZwNFhwWT89fAFr&t=0s

CNN Playlist: https://www.youtube.com/watch?v=E5Z7FQp7AQQ&list=PLuhqtP7jdD8CD6rOWy20INGM44kULvrHu&t=0s

Complete Neural Network: https://www.youtube.com/watch?v=mlk0rddP3L4&list=PLuhqtP7jdD8CftMk831qdE8BlIteSaNzD&t=0s

Complete Logistic Regression Playlist: https://www.youtube.com/watch?v=U1omz0B9FTw&list=PLuhqtP7jdD8Chy7QIo5U0zzKP8-emLdny&t=0s

Complete Linear Regression Playlist: https://www.youtube.com/watch?v=nwD5U2WxTdk&list=PLuhqtP7jdD8AFocJuxC6_Zz0HepAWL9cF&t=0s