Data Science, Python, Machine Learning, Dimensionality Reduction.
original high dimensional data into a lower dimensional space, while preserving most of the variance. This is accomplished by applying a linear orthogonal transformation to a different system of coordinates, where the first principal component explain most of the data variance. PCA helps us