VGG16 for Image Classification

This repository provides a detailed implementation of VGG16, a deep CNN architecture known for its simplicity and effectiveness in image classification tasks. VGG16 is composed of 16 layers, including convolutional and fully connected layers. The project includes pre-trained weights for classifying images on popular datasets like ImageNet and CIFAR-10. The repository also demonstrates techniques such as transfer learning, fine-tuning, and model evaluation on custom datasets.