Deep Dive into the Transformer Encoder Architecture

Introduction
Encoder Overview
Blowing up the encoder
Create Initial Embeddings
Positional Encodings
The Encoder Layer Begins
Query, Key, Value Vectors
Constructing Self Attention Matrix
Why scaling and Softmax?
Combining Attention heads
Residual Connections Skip Connections
Layer Normalization
Why Linear Layers, ReLU, Dropout
Complete the Encoder Layer
Final Word Embeddings
Sneak Peak of Code