We dive into Transformers in Deep Learning, a revolutionary architecture that powers today's cutting-edge models like GPT and BERT. We’ll break down the core concepts behind attention mechanisms, self-attention, and how Transformers handle sequential data. We will see the limitations of RNNs, and why Transformers are so powerful.

This is a 1st part of my Transformers in Deep Learning Course, providing an overview of Transformers, and its importance.

Whether you're a beginner or looking to deepen your understanding, my Transformers in Deep Learning Course playlist will guide you through the in-depth working of Transformers.



Timestamps:
0:00 Intro
1:55 RNN Limitations
4:44 Why Word Embedding is a problem?
7:20 Self Attention Overview
11:57 Scale of Transformers?
12:54 Parallelisation in Transformers
15:21 Transfer Learning in Transformers
18:55 Multi-modality in Transformers
20:28 Outro



Follow my entire playlist on Recurrent Neural Network (RNN) :

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



If you want to ride on the Lane of Machine Learning, then Subscribe to my channel here: https://www.youtube.com/channel/UCJFAF6IsaMkzHBDdfriY-yQ?sub_confirmation=1