MLGrind - Master Machine Learning

Why this matters:

Tests understanding of linear algebra and dimensionality reduction – critical for data preprocessing roles.

PCA is a dimensionality reduction technique that finds the directions of maximum variance in the data and projects the data onto these directions.

Your implementation should:

Center the data

Compute the covariance matrix

Find eigenvalues and eigenvectors

Project data onto top k components

Principal Component Analysis