The ROC Curve (Receiver-Operating Characteristic Curve) — Topic 84 of Machine Learning Foundations

#MLFoundations #Calculus #MachineLearning In this video, we work through a simple example — with real numbers — to demonstrate how to calculate the Receiver-Operating Characteristic Curve (the ROC Curve), an enormously useful metric for quantifying the performance of a binary classification model. There are eight subjects covered comprehensively in the ML Foundations series and this video is from the fourth subject, “Calculus II: Partial Derivatives & Integrals“. More detail about the series and all of the associated open-source code is available at The playlist for the Calculus subjects is here: Jon Krohn is Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the industry’s most listened-to podcast. Jon is renowned for his compelling lectures, whic