I built a deep learning model to classify various skin conditions from image data. Using augmentation and careful preprocessing, I trained both a custom CNN and fine-tuned a Keras model, then compared their performance across multiple datasets. The result: high accuracy classification and insights into which architectures work best for this medical imaging task.