{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/0485dcd5917944cea6c63072f3558c5c\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/0485dcd5917944cea6c63072f3558c5c-34cca850588d7a37.gif","duration":114.886,"title":"Building a Fraud Model for DoorDash","description":"In this video, I walk you through the steps to build a fraud model aimed at reducing fraudulent consumer accounts for DoorDash. We will be using a provided CSV file containing historical data, which includes a fraud indicator and various aggregated variables. I outline the necessary steps, including exploratory data analysis, data preparation, feature extraction, and model selection. Please make sure to follow these steps closely as you work on the project."}