Course 13 High Dimensional Data Analysis

High-dimensional data analysis is a rapidly growing field that deals with datasets containing a large number of variables or features, often far exceeding the number of observations. As modern technologies and scientific advancements generate vast amounts of complex data, understanding and extracting meaningful patterns from high-dimensional spaces has become paramount. The challenges in analyzing such data arise from issues like the “curse of dimensionality,” where traditional statistical methods struggle to cope with the increased complexity and risk of overfitting. This section explores various techniques, including dimension reduction, regularization, and machine learning methods, to effectively analyze and interpret high-dimensional data, with applications across fields such as genomics, finance, and image processing.