{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/e7d952a803904c26b0e9fbd0f2164f3c\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/e7d952a803904c26b0e9fbd0f2164f3c-b189f319c73c10f5.gif","duration":300.134,"title":"ML App with Django to create and deploy models using Zenml and MLflow","description":"In this video, I demonstrate my machine learning app using Zenml and MLflow to train a model and deploy it as an endpoint. I upload a CSV file, select viscosity as the target variable, and use a lasso model for training. After registering the model in our MLflow server, I show how to deploy it and invoke predictions with different input values. I encourage you to explore the app and test various parameters to see how it performs. Please let me know if you have any questions or need further assistance."}