{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/8da5e7ae5a6144d4bc85ceacebcd6419\" 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/8da5e7ae5a6144d4bc85ceacebcd6419-1707154726368.gif","duration":232.98,"title":"Building a Creative Recognition System","description":"In this video, I walk through the process of building a creative recognition system using a binary classification model. I explain how I collected and labeled the dataset, imported the necessary libraries, defined the directory, and used an image data generator. I then demonstrate how I trained the model using a CNN architecture and evaluated its accuracy. Finally, I show how to deploy the system using Streamlit and test it with different images. No action is requested from the viewers, but I encourage you to watch and learn about the process!"}