---
title: "Discussion on \"Step-By-Step Guide to Measuring Relevance in Azure AI Search\" | Hashnode"
description: "Discussion on \"Step-By-Step Guide to Measuring Relevance in Azure AI Search\". Optimizing Retrieval Systems with Cohere Embeddings and the WANDS Dataset"
url: "https://hashnode.com/posts/step-by-step-guide-to-measuring-azure-ai-search-relevance-the-hello-world-of-information-retrieval/6716eda103f61e8407447ab8"
---

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# [Step-By-Step Guide to Measuring Relevance in Azure AI Search](https://farzzy.hashnode.dev/step-by-step-guide-to-measuring-azure-ai-search-relevance-the-hello-world-of-information-retrieval?utm_source=hashnode&utm_medium=feed)

Optimizing Retrieval Systems with Cohere Embeddings and the WANDS Dataset

Oct 22, 2024 · 15 min read · farzzy.hashnode.dev  
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-   [#search-relevance](https://hashnode.com/tag/search-relevance)
-   [#ranx](https://hashnode.com/tag/ranx)
-   [#cohere](https://hashnode.com/tag/cohere)
-   [#azure-ai-search](https://hashnode.com/tag/azure-ai-search)
-   [#vector-embeddings](https://hashnode.com/tag/vector-embeddings)

## Written by

[Farzad Sunavala](https://hashnode.com/@Farzzy528)

@Farzzy528 · Remote, US

  
[View profile](https://hashnode.com/@Farzzy528)

I build Generative AI stuff...

Principal Product Manager at Microsoft CoreAI leading Retrieval-Augmented Generation (RAG) and knowledge retrieval capabilities, powering enterprise AI applications with grounded, production-scale search and retrieval.

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