Dimensionality reduction is a technique employed in machine learning and data analysis to condense large datasets while preserving the most significant information. Modern datasets often contain hundreds or even thousands of features. Working with such high dimensional data can slow down algorithms, increase storage needs, and make patterns harder to detect. Learning these concepts is […]