Practical Data Science using Python - K-Means - Model Optimization

The video tutorial explains the process of clustering using the K-means algorithm, focusing on label assignment, pivot table creation, and mean calculation. It highlights the challenges of using categorical variables in clustering and demonstrates how to visualize clusters in 3D using Matplotlib. The tutorial also covers dimensionality reduction techniques like PCA and TSNE to handle high-dimensional data. Finally, it discusses the application of clustering for customer segmentation, emphasizing the importance of tailored promotions for different customer groups.

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