Retrieval Evaluation / Conclusion
Retrieval Evaluation
Excellent work! You learned how to:
Learning Objectives
Benchmark embedding models using a golden dataset: Identify the three components of a test collection (corpus, queries, and relevance judgments).
Interpret core retrieval evaluation metrics: Explain what Recall@k, MRR, and NDCG@k each measure and what each metric reveals about an embedding model's retrieval quality.
Evaluate and compare retrieval strategies using real benchmark data: Read MS MARCO and MIRACL benchmark results in context, run a structured evaluation across lexical, vector, and hybrid search, and use metric results to make a justified model selection decision.
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Resources
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