People have consistently been able to perceive and recognize faces and their feelings. Presently PCs can do likewise. We propose a model which recognizes human faces and classifies the emotion on the face as happy, angry, sad, neutral, surprise, disgust or fear. It is developed utilizing a convolutional neural network(CNN) and involves various stages. All these are carried out using a dataset available on the Kaggle repository named fer2013. Precision and execution of the neural system can be assessed utilizing a confusion matrix. We applied cross-approval to decide the ideal hyper-parameters and assessed the presentation of the created models by looking at their training histories.