Overview Hey This project implements a Convolutional Neural Network (CNN) to detect human emotions from facial expressions. The model is trained on a Kaggle dataset and uses deep learning techniques to classify images into different emotion categories.
Features:
CNN Architecture: Custom-built deep learning model for emotion classification. Data Preprocessing: Image normalization and resizing. Data Augmentation: Techniques like flipping, rotation, and zooming to improve generalization. Model Training: Utilized deep learning frameworks to optimize accuracy. Performance Evaluation: Metrics such as accuracy and loss visualization.
Technologies Used:
Python TensorFlow/Keras NumPy & Pandas Matplotlib