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Constructing Self Attention Matrix
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Classroom Contents
Deep Dive into the Transformer Encoder Architecture
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- 1 Introduction
- 2 Encoder Overview
- 3 Blowing up the encoder
- 4 Create Initial Embeddings
- 5 Positional Encodings
- 6 The Encoder Layer Begins
- 7 Query, Key, Value Vectors
- 8 Constructing Self Attention Matrix
- 9 Why scaling and Softmax?
- 10 Combining Attention heads
- 11 Residual Connections Skip Connections
- 12 Layer Normalization
- 13 Why Linear Layers, ReLU, Dropout
- 14 Complete the Encoder Layer
- 15 Final Word Embeddings
- 16 Sneak Peak of Code
