Image Classification with Transfer Learning: Classifying Dog Breeds Using Python
Imagine having an AI that instantly tells you the breed of any dog you encounter! In this tutorial, we'll use Transfer Learning to build a powerful image classifier capable of recognizing dog breeds from photos, even with limited training data. What is Transfer Learning? Transfer Learning allows you to leverage pre-trained neural networks (trained on millions of images) and adapt them for your specific task, significantly reducing the time and data needed to train your model. Let's Get Started! Step 1: Setup Your Environment Ensure you have TensorFlow and Keras installed: pip install tensorflow matplotlib Step 2: Prepare Your Dataset We'll use the popular Stanford Dogs Dataset . It contains thousands of images across 120 dog breeds. Organize your dataset: data/ train/ breed1/ breed2/ ... validation/ breed1/ breed2/ ... for this we need to execute the next command: ! wget http://vision . stanford . edu/aditya86/ImageNetDogs/images . tar After t...
