video1.0<iframe src="https://www.loom.com/embed/6e793e34688a490abcec2042f664325d" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/6e793e34688a490abcec2042f664325d-a481e073b56a8e90.gif240.027Hi everyone, in this video, I present my MLO summative project where I built a Fisher recognition web app using the V2A mobile app and deployed it with a public URL. I demonstrate how to upload images, showing that I successfully uploaded three pictures of 'blurry' and three of 'Justin.' The model retraining process is highlighted, with a distribution of 10 images for blurry and 9 for Justin, achieving an accuracy of 38% after 30 training sessions. I also showcase the prediction feature, where the app identified an uploaded image with a confidence of 61.41% for Justin and 15.2% for blurry. Thanks for your attention, and I encourage you to try uploading images and see the predictions for yourself!