39. HIERARCHICAL CLUSTERING

Hierarchical clustering is an unsupervised machine learning technique used to group similar data points into clusters based on a hierarchy. It builds a tree-like structure called a dendrogram, which shows how clusters are merged or split at different levels. The algorithm can be agglomerative (bottom-up) or divisive (top-down). It doesn't require specifying the number of clusters in advance, making it useful for exploratory data analysis.

📂 Resources:
🔗 Colab Notebook: https://colab.research.google.com/drive/1AjP96UC9QSTnZBcm-BTlGQpYreFq9WlG?usp=sharing
Open Notebook

📄 Document/Notes (PDF): https://presenti.ai/app/share/CAE.IAEqECsA_ZfciHA3BtBTSC77n7owAUABSgoxNzUxNzE5NjEw?invite_code=v535Rxxj&autoPresent=true%EF%BC%8C
View/Download Notes

🧪 Dataset (if any): https://drive.google.com/file/d/1ZPRaLEnp_zNAsOMUv0dmM_VvbpGSudzh/view?usp=sharing
Download Dataset

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Видео 39. HIERARCHICAL CLUSTERING канала Kiet-Hub