Facial Expression Recognition A deep learning and computer vision project to guess the state of emotion of humans based on facial expressions Implemented using pytorch framework used efficientnet-b0 architecture for CNN for training the model Used cuda to decrease the training time per epoch from around 10 mins to under 1 min Gained approx. 65% accuracy on test set used OpenCV for reading and pre-processing images randomly augmented the images by flipping and rotating images to increase test accuracy