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Clustering

Data:

Two data sets: offers details and customer transactions associated with offers.

Approach:

This project utilizes Sklearn to demonstrate various clustering techniques including K-means, DBSCAN, Spectral Clustering, Affinity Propagation, and Agglomerative Clustering. Relevant methods for selecting number of clusters in K-means, namely the Elbow method and the Silhouette Coefficient were also tested.

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K-means, DBSCAN, Spectral Clustering, Affinity Propagation, and Agglomerative Clustering (scikit-learn)

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