PART IV — Embeddings: Turning Tokens into Meaning

 

Chapter 7: Embeddings and Vector Representations

Goal: Explain how meaning is stored

Topics Covered:

• What embeddings are

• Dense vector spaces

• Semantic similarity

• Contextual vs static embeddings

• Embedding matrix learning

📌 Medium Post 7: Embeddings: Where Meaning Begins