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mlmentorship

Book VI · Chapter 1

Retrieval foundations

Move from sparse retrieval and embeddings to approximate search and two-tower systems.

Priority
Role-specific
Difficulty
Intermediate
Useful for
Ranking MLE, AS, MLE
Interview rounds
Retrieval, ML design

Chapter contents

6 entries · read in order
  1. 01
    TF-IDF and BM25
    Concept
  2. 02
    Embedding spaces and similarity metrics
    Concept
  3. 03
    Approximate nearest neighbors: HNSW, IVF, and product quantization
    Concept
  4. 04
    Two-tower retrieval
    Concept
  5. 05
    Knowledge-graph embeddings
    Concept
  6. 06
    Content-based filtering
    Concept