This project tackles the Histopathologic Cancer Detection challenge by building a deep learning model to classify histopathology images as cancerous or non-cancerous. A CNN model is trained using data augmentation and preprocessing, evaluated with ROC-AUC, and generates probability-based predictions for submission. 🚀

This notebook is for the Kaggle competition on detecting metastatic cancer in small histopathologic image patches. The goal is to build a binary classification model to predict the probability of tumor presence in each image.