Data Scientist Dismantles the YouTube Algorithm.

In this video I walk you through some of the specifics of the YouTube Algorithm. My background as a data scientist can help you better understand this algorithm and increase your chances of having it pick your videos up. The algorithm wants you to watch YouTube for as long as possible. It prioritizes videos that have a high click through rate (CTR) and high watch time. When you combine these two metrics you get Expected watch time. This is the variable that the algorithm is trying to optimize for with each recommendation. Jarvis Johnson Video: https://www.youtube.com/watch?v=2GYXemlyd_Q YouTube Algo White Paper: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45530.pdf More on the Algo: https://www.tubefilter.com/2017/02/16/youtube-algorithm-reverse-engineering-part-ii/ Another good Algo Resource: https://ammar-alyousfi.com/2020/youtube-trending-videos-analysis-2019-us The model uses a two phased deep neural net architecture. The first phase takes millions of videos and filters them to less than 1000 relevant videos. The next phase ranks the smaller group of videos based on more specific metrics that youtube has access to. Take aways for growth: 1) Maximize Expected Watch time 2) Give viewers a reason to watch to the end 3) Make videos similar to others in a specific domain 4) Optimize videos for the 3rd day 5) Tweak things periodically to capitalize on A/B testing #DataScience #KenJee #YouTubeAlgorithm #DataScience #KenJee ⭕ Subscribe: https://www.youtube.com/c/kenjee1?sub_confirmation=1 🎙 Listen to My Podcast: https://www.youtube.com/c/KensNearestNeighborsPodcast 🕸 Check out My Website - https://kennethjee.com/ ✍️Sign up for My Newsletter - https://www.kennethjee.com/newsletter 📚 Books and Products I use - https://www.amazon.com/shop/kenjee (affiliate link) Partners & Affiliates 🌟 365 Data Science - Courses ( 57% Annual Discount): https://365datascience.pxf.io/P0jbBY 🌟 Interview Query - https://www.interviewquery.