Self Attention is a mechanism that enables transformers to weigh the importance of different words in a sequence relative to each other. It allows the model to focus on relevant information, improving its ability to capture long-range dependencies in data.
Digital Notes for Deep Learning: https://shorturl.at/NGtXg
============================
Do you want to learn from me?
Check my affordable mentorship program at : https://learnwith.campusx.in/s/store
============================
📱 Grow with us:
CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official
CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official
My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789
Discord: https://discord.gg/PsWu8R87Z8
E-mail us at [email protected]
✨ Hashtags✨
#SelfAttention #DeepLearning #CampusX #NLP
⌚Time Stamps⌚
00:00 - Intro
01:50 - What is Self Attention?
11:41 - The problem of "Average Meaning"
22:46 - Outro