This project confronts the global challenge of colorectal cancer (CRC), a leading cause of cancer-related deaths. We aim to elevate CRC detection from histological images, capitalizing on the potential of machine learning with the "NCT-CRC-HE-100K" dataset. The end goal is not just to benchmark but also to deploy a user-centric web application for practical use. The dataset comprised 100,000 distinct non-overlapping image patches from H&E stained histological images, providing a rich source for analysis.