video1.0<iframe src="https://www.loom.com/embed/d4cd5c04379e4472a57fdf2ea78e5a19" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/d4cd5c04379e4472a57fdf2ea78e5a19-ae65cf862fc0a2f5.gif150.9615In this video, I present my project on predicting rental apartment prices in Israel using real market data. I analyzed the rental market and user needs, parsed data from Yachtstein, and built a relational database with 19 linked tables for scalability. After testing several machine learning models, I found that PadBoost provided the best accuracy for predictions. I also developed a Telegram bot with GeoIP functionality, allowing users to get predictions based on their location. I encourage viewers to explore the dashboard I created to visualize prices and trends.