In this challenge, we learned how machine learning can be applied to medical imaging. we use the human gastrointestinal (GI) tract endoscopic imagery in order to detect different anomaly types.
During this task we explored KVASIR dataset.
We trained a classification model on the given medical dataset to classify anomalies in Gastrointestinal Tract using endoscopic imagery. We used a Deep Convolutional Neural Network with transfer learning.