Transformer Encoder Explained with Visuals | Attention, Embedding, PE, Residual Connections

Build AI with Sandeep · Beginner ·🧠 Large Language Models ·7mo ago

Key Takeaways

This video teaches the Transformer Encoder architecture, including attention, embedding, positional encoding, and residual connections

Original Description

Welcome to Build AI with Sandeep! In this video, we will understand the complete Transformer Encoder architecture in a very simple and visual way — no complex math, no confusion. 🔹 What you will learn in this video: ✔ Word Embedding & Tokenization ✔ Positional Encoding (Why and How?) ✔ Scaled Dot-Product Attention (Simple explanation) ✔ Multi-Head Self Attention ✔ Add & Norm (Residual Connections + LayerNorm) ✔ Feed Forward Neural Network ✔ Final Encoder Output (Contextual Embedding)
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