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

#MLFoundations #Calculus #MachineLearning

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.

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 leading industry conferences, as well as online via O'Reilly, his YouTube channel, and the SuperDataScience podcast.

[justsimple]

I don't understand why no change occurs if I don't cancel du from dy/du * du/dx.