Sin_cancer_project

This project focuses on building a deep learning model for skin cancer classification using dermoscopic images.

The goal is to classify images into benign or malignant categories using Convolutional Neural Networks (CNN) and transfer learning techniques such as MobileNetV2.

The workflow includes data preprocessing, augmentation, model training, fine-tuning, and evaluation using accuracy and other performance metrics.

The final model can be deployed using Streamlit for real-time prediction.