In this episode I tried to explain the principle behind face regonition using PCA -Eigen face Approach PCA- Principal Component Analysis Eigen faces:  An eigenface is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition. What is eigenvalues and eigenvectors in PCA? Eigenvectors are unit vectors with length or magnitude equal to 1. ...  Eigenvalues are coefficients applied to eigenvectors that give the vectors their length or magnitude.  Covariance Matrix:is a square matrix giving the covariance between each pair of elements of a given random vector. Listen the episode on all podcast platform and share your feedback as comments here  Do check the episode on various platform follow me on instagram  https://www.instagram.com/podcasteramit  Apple https://podcasts.apple.com/us/podcast/id1544510362  Huhopper Platform https://hubhopper.com/podcast/tech-stories/318515  Amazon https://music.amazon.com/podcasts/2fdb5c45-2016-459e-ba6a-3cbae5a1fa4d  Spotify https://open.spotify.com/show/2GhCrAjQuVMFYBq8GbLbwa