Data Science Clustering

Stockholm University

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Data Science- Clustering
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9

January 2026

2025/2026
The document is organized as a lecture-style summary or set of notes intended to explain clustering algorithms, their mechanics, use cases, strengths, and weaknesses. It is divided into clear sections, each building upon the previous, and uses a memorable party/popular kid analogy to anchor the abstract concepts of clustering in a relatable narrative. Key characteristics of the document: · Pedagogical Approach: Uses strong analogies (e.g., party groups, popular kids) to explain complex al...
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