Snacks Weekly on Data Science

Pan Wu

This podcast is about making data science and machine learning knowledge accessible and less intimidating. Every week, I will handpick one selected industrial tech blog to break it down. We will discuss some key data science concepts and machine learning algorithms, and how they are applied in those real-world applications. Subscribe to the channel and enjoy Snacks Weekly on Data Science!

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Snacks Weekly on Data Science

Episodes (140)

Monday Building Taxonomies with Large Language Models [Microsoft]
Mon May 18th Fraud Detection with Multi-Agent AI Architecture [Razorpay]
Mon May 11th Hybrid Search for Improved Content Discovery [OLX]

Snacks Weekly on Data Science

May 25, 2026
9 minutes
12 MB

In this episode, we look at how companies deal with large volumes of unstructured text and why traditional clustering methods often fall short at scale. We explore two LLM-powered approaches shared by data scientists from Microsoft: a bottom-up pipeline that builds structure from data using embeddings and clustering, and a top-down pipeline that starts with LLM-generated categories and refines them recursively into a hierarchy. For more details, you can refer to their published tech blog, linked here for your reference: https://medium.com/data-science-at-microsoft/from-chaos-to-clarity-building-taxonomies-from-unstructured-text-using-large-language-models-c1303db3adb1

Snacks Weekly on Data Science

Building Taxonomies with Large Language Models [Microsoft]

Pan Wu

00:00 -08:41