{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/813d03b9de5844f2b060a5d410245f98\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/813d03b9de5844f2b060a5d410245f98-1720459510726.gif","duration":637.685,"title":"Bias Bounty 101 for Beginners 🤖 Video 3 - Creating Categories","description":"Join me in this tutorial series to learn about Humane Intelligence's bias bounty challenge. I cover how to use spaCy, a Python library, to analyze the text from our filtered DataFrames and then provide step-by-step code on how to extract the Named Entities from each conversation.\n\nVideo 3 Jupyter Notebook: https://bit.ly/3zBTmun\n\nDid you miss Video 1 - Accessing the Data? Watch it here: https://bit.ly/45Vp1TE\nDid you miss Video 2 - Inspecting the Data? Watch it here: https://bit.ly/3RYEb4Q"}