video1.0<iframe src="https://www.loom.com/embed/f1c8a11cd25a431da79b71eed1b65b2c" frameborder="0" width="1514" height="1135" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>11351514Loomhttps://www.loom.com11351514https://cdn.loom.com/sessions/thumbnails/f1c8a11cd25a431da79b71eed1b65b2c-c8a875a9e6b2f94b.gif270.747In this video, I demonstrate my web app, Biggie-D-O, which classifies Python code based on its runtime complexity in big-O notation. I showcase examples like merge sort and bubble sort, highlighting the app's speed and accuracy in providing the correct complexity analysis. The model I developed achieved an 88% F1 macro score using a deep learning approach with 1.3 billion parameters. I utilized existing datasets and conducted thorough model selection and fine-tuning. I encourage viewers to check out the links in my repository for more details and insights on the project.