Mathematics, Linear Algebra, Machine Learning, Data Science.
useful in dimensionality reduction, which is commonly used when dealing with high-dimensional data. The idea behind it is that high-dimensional data often has some underlying structure that can be captured by a lower-dimensional representation. One of the most popular techniques for dimensionality