Clustering is one of the fundamental machine learning techniques that allows you to solve many complex problems in real life: market segmentation, anomaly detection, dimensionality reduction, revealing hidden patterns, etc.

First of all, let's understand what is clustering, why we need it, and consider some unique concepts about clustering problems. We will also look at the classification of clustering algorithms according to the principle of their work.

Now let's look at the most popular clustering algorithms in more detail: we will understand the principles of their work, look at their implementation in Python, and have some practice in solving simple tasks using these algorithms.

Finally, we will understand how to choose the best model and solve real tasks based on evaluation metrics and other validation techniques. 

Perform Agglomerative Clustering

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Perform Agglomerative Clustering

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