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Reducing Complexity in Primary Education Data for Enhanced Analysis
This project focuses on applying dimension reduction techniques—Principal Component Analysis (PCA) and Multidimensional Scaling (MDS)—to a dataset related to primary education, obtained from UNICEF. The aim is to understand patterns in the data while reducing its dimensional complexity for efficient analysis.