The Chain Rule for Derivatives — Topic 59 of Machine Learning Foundations

#MLFoundations #Calculus #DataScience This video introduces the chain rule, which is arguably the single most important differentiation rule for machine learning. It facilitates several of the most ubiquitous ML algorithms, such as gradient descent and backpropagation — algorithms we detail later in this video series. There are eight subjects covered comprehensively in the ML Foundations series and this video is from the third subject, “Calculus I: Limits & Derivatives“. 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 untapt. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University, New York University, and lead