video1.0<iframe src="https://www.loom.com/embed/07abc76e62594bc3b389eb7b8f2d00d9" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/07abc76e62594bc3b389eb7b8f2d00d9-7111b79de83a4d16.gif181.033333This is my third project built with Flask, a fake news detection system using an ML model trained on real and fake news data. I show the localhost web app with a light and dark theme and a page where you can paste a suspicious headline or article. The model analyzes the text and gives the probability and labels it as real, fake, or suspicious across three categories. For example, when I entered “double your money 2 hours,” it returned about 29.5 real and 14% fake. I do not ask viewers for a specific action, just to try entering their own headlines.