Eigenvectors, Principal Component, Dimensionality Reduction, Data Science, Unsupervised Learning.
random line and keeps rotating until the line best fits the data given that the line has to pass through the origin. Source: Image by Author Step 2: Ultimately it finds the best fit line which explains maximum variation Source: Image by Author 3. So, How does PCA arrive at the best fit line? To