{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/953d824f72234de88ff0cf7e3e92ac09\" frameborder=\"0\" width=\"1662\" height=\"1246\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1246,"width":1662,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1246,"thumbnail_width":1662,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/953d824f72234de88ff0cf7e3e92ac09-17e98c756a8024b3.gif","duration":111.591,"title":"Revolutionizing Data Science Workflows with Autonomous Agents 🤖","description":"In this video, I introduce our ML agent, an autonomous multi-agent system designed to streamline the workflow of data scientists, who typically spend 80% of their time on repetitive tasks. By automatically gathering context from sources like Google Scholar, GitHub, and Hugging Face, our system enhances efficiency. I demonstrate how, after uploading a dataset, our agent system employs a manager agent to coordinate various specialized agents that analyze the data, find relevant research, and develop a machine learning model with optimal results. I encourage you to explore this innovative tool to improve your data analysis processes. Please let me know your thoughts or questions!"}