The repository contains the python jupyter notebook and the report.
In more recent years Face Recognition introduced itself in our lives. We use it almost every day and sometimes without even noticing anymore. For example, whenever we post something on Facebook or import a picture inn Apple’s Photo app, the software automatically recognizes the faces and assigns labels. Also, the newest smartphones have face recognition as the main security option for accessing the device. In some states, face recognition is even used to reduce crime and prevent violence in the streets. Since there are so many everyday life uses these software have to be able to recognize and handle the problems deriving from having different backgrounds, facial expressions or light conditions. Therefore, face recognition has become a common problem in Machine Learning, and it has been approached in different ways. One of the simplest techniques is eigenfaces: it is quite efficient, and it usually generates good results. Face recognition consists in two main phases: one is about finding the main features of the images and the second step is the one that classifies the various pictures as belonging to one determined person or another.