Face recognition in artificial intelligence is a frequent problem. This application was extensively used in our daily life. Several smartphones were opening phones with facial identification to safeguard private details and used on Facebook to identify instantly when users of Facebook appear in pictures. Several approaches for face recognition have already been suggested until now, but it remains very difficult in real-world situations. A primary technique to differentiate people depends on various conditions, for example, partial facial occlusion, illumination, and posture variety. This paper aims at designing a face recognition approach utilizing machine learning algorithm and principal component analysis (PCA). It is experimented using linear discriminant analysis, multilayer perceptron, Naive Bayes, and support vector machine. Moreover, it has achieved recognition accuracy of 97% & 100% by using PCA and linear discriminant analysis.