Fundamentals
Fundamentals of embeddings: what they’re, how they work, why they’re so highly effective and the way they’re created.
Embeddings are the cornerstone of many AI and ML functions, resembling GenAI, RAG, recommender methods, encoding high-dimensional categorical variables (resembling enter tokens for LLMs) and extra.
For instance, in an RAG utility, they play a pivotal position in indexing and retrieving knowledge from the vector DB, immediately impacting the retrieval step.
They’re current in nearly each ML area in a single type or one other.
Thus, having a robust instinct of how embeddings work is a highly effective talent.
On this article, you’ll study concerning the fundamentals of embeddings, resembling:
- what they’re
- how they work
- why they’re so highly effective
- how they’re created.
- What are embeddings
- Why embeddings are so highly effective
- How are embeddings created?
- Purposes of embeddings