Attention Is All You Need - Paper Explained
In this video, I'll try to present a comprehensive study on Ashish Vaswani and his coauthors' renowned paper, “attention is all you need”
This paper is a major turning point in deep learning research. The transformer architecture, which was introduced in this paper, is now used in a variety of state-of-the-art models in natural language processing and beyond.
📑 Chapters:
0:00 Abstract
0:39 Introduction
2:44 Model Details
3:20 Encoder
3:30 Input Embedding
5:22 Positional Encoding
11:05 Self-Attention
15:38 Multi-Head Attention
17:31 Add and Layer Normalization
20:38 Feed Forward NN
23:40 Decoder
23:44 Decoder in Training and Testing Phase
27:31 Masked Multi-Head Attention
30:03 Encoder-decoder Self-Attention
33:19 Results
35:37 Conclusion
📝 Link to the paper:
https://arxiv.org/abs/1706.03762
👥 Authors:
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin
🔗 Helpful Links:
"Vectoring Words (Word Embeddings)" by Computerphile:
• Vectoring Words (Word Embeddings) - Comput...
"Transformer Architecture: The Positional Encoding" by Amirhossein Kazemnejad:
https://kazemnejad.com/blog/transform...
"The Illustrated Transformer" by Jay Alammar:
https://jalammar.github.io/illustrate...
Lennart Svensson's Video on Masked self-attention:
• Transformers - Part 7 - Decoder (2): maske...
Lennart Svensson's Video on Encoder-decoder self-attention:
• Transformer - Part 8 - Decoder (3): Encode...
🙏 I'd like to express my gratitude to Dr. Nasersharif, my supervisor, for suggesting this paper to me.
🙋♂️ Find me on: halflingwizard.me
🎁 Support the Channel:
If you’d like to support my work, you can check out my wishlist here: https://www.amazon.com/registries/gl/...
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#Transformer #Attention #Deep_Learning