CNN Project

Built and trained a Deep Learning model using Convolutional Neural Networks (CNN) for automated image classification. The project focused on optimizing the architecture to prevent overfitting by implementing Dropout layers and Data Augmentation techniques. The model was evaluated using accuracy and loss curves to ensure stable convergence and high generalization on unseen data.