Use a Pre-trained Image Classifier to Identify Dog Breeds

Overview : This project uses a pre-trained image classifier to identify dog breeds from images. The objective is to apply deep learning and transfer learning techniques to classify images of dogs into their respective breeds. The project utilizes well-known architectures such as VGG16, ResNet, and Inception, leveraging their pre-trained weights to extract features from new images and determine the breed.

Requirements : Python 3.7 or later

TensorFlow 2. x

Additional libraries: numpy, matplotlib, opencv-python, PIL

Acknowledgments : Part of the "AI Programming with Python and TensorFlow" course from Udacity.

Uses established neural network architectures for effective classification.