Machine Learning - Logistic Regression Details Pt 2: Maximum Likelihood

This video follows from where we left off in Part 1 in this series on the details of Logistic Regression. This time we're going to talk about how the squiggly line is optimized to best fit the data. NOTE: This StatQuest assumes that you are already familiar with Part 1 in this series, Logistic Regression Details Pt1: Coefficients: https://youtu.be/vN5cNN2-HWE For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #logistic #MLE