Transformer Architecture | Part 1 Encoder Architecture | CampusX
The Encoder in transformer architecture processes input sequences by applying layers of multi-head self-attention and feed-forward networks. Each layer consists of self-attention mechanisms followed by layer normalization and feed-forward neural networks. This architecture enables the model to capture complex patterns and relationships in the input data, facilitating tasks like language translation and text summarization. Notes: https://learnwith.campusx.in/s/store/... ============================ Did you like my teaching style? Check my affordable mentorship program at : https://learnwith.campusx.in DSMP FAQ: https://docs.google.com/document/d/1O... ============================ 📱 Grow with us: CampusX' LinkedIn:   / campusx-official  Slide into our DMs:   / campusx.official  My LinkedIn:   / nitish-singh-03412789  Discord:   / discord  E-mail us at [email protected] ✨ Hashtags✨ #campusx #deeplearning #transformers ⌚Time Stamps⌚ 00:00 - Intro 02:36 - Recap/Prerequisite 05:10 - Understanding Architecture 13:02 - Encoder Architecture 28:50 - Encoder - Feed Forward Network 41:39 - Some Questions 54:45 - Outro
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