Emotion Detection using CNN (FER2013 Dataset)

Developing a deep learning model to detect human emotions from facial images using a Convolutional Neural Network (CNN).

We use the FER2013 dataset from Kaggle, which contains over 35,000 grayscale images of faces, each labeled with one of seven emotions: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral.

The goal is to train a CNN to recognize these emotions accurately from unseen images.