How to Gather Data from YouTube

Since its 2005 inception, YouTube has entertained, educated, and inspired more than one billion people. It now ranks as the 2nd most visited website on the planet, and its users upload 300 hours of video content every minute. YouTube clearly dominates as the world’s premier source of cute baby moments, epic sports fails, and hilarious cat videos, but its vast troves of content can also be leverage to strengthen a wide variety of data science projects. In this post, I share how you can gain access to three types of YouTube data: the videos themselves for use in computer vision tasks, the video transcripts for natural language processing (NLP), and video search results for hybrid machine learning efforts.

Please continue to the Metis blog to read my full post covering data collection from YouTube.