Detecting Power Laws in Real-world Data | w/ Python Code

🤝 Want your team maximizing Claude? I run 1:1 and team AI workshops for companies doing $1M+ per year: https://aibuilder.academy/yt/x5-IW1m3zPo This is the 2nd video in a series about Power Laws and Fat Tails. In this video, I describe how to objectively detect Power Laws from real-world data and share a concrete example with social media data. 📹 Series Intro: https://youtu.be/Wcqt49dXtm8 📹 Fat Tails: https://youtu.be/15Kd9OPn7tw 📰 Read more: https://medium.com/towards-data-science/detecting-power-laws-in-real-world-data-with-python-b464190fade6?sk=07960e2c880b7f6f5ac577e6beb843a3 💻 GitHub Repo: https://github.com/ShawhinT/YouTube-Blog/tree/main/power-laws/2-detecting-powerlaws References [1] arXiv:0706.1062 [physics.data-an] [2] arXiv:2001.10488 [stat.OT] [3] https://en.wikipedia.org/wiki/Likelihood_function [4] https://en.wikipedia.org/wiki/Pareto_distribution Intro - 0:00 Power Laws Break STAT 101 - 0:59 Log-Log Approach - 2:21 Maximum Likelihood Approach - 4:54 Example Code: Artificial Data - 8:11 Example Code: Real-world Social Media Data - 16:16 What's Next? - 22:29