video1.0<iframe src="https://www.loom.com/embed/8f48ec618e6948bba0104f056e35a7cd" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/8f48ec618e6948bba0104f056e35a7cd-fd46dedb2e2d5a3c.gif170.142In this video, I present my lead scoring tool developed for the Capre Capital AI readiness challenge, aimed at helping marketing teams predict lead conversions and optimize resource allocation. I built a machine learning model using real-world data, comparing multiple models, and found that XGBBoost achieved over 90% accuracy. I demonstrate how to use the app deployed on the Streamlit platform, where users can upload a CSV file to get predictions on lead conversions. I encourage you to check out the GitHub repository for all the necessary files related to this project. If you have any questions, feel free to reach out!