Intro to Deep Learning and Generative Models Course - L5.5 (Optional) Calculus Refresher II: Gradients

Sebastian's books: https://sebastianraschka.com/books/ Now that we covered derivatives, let's add another dimension to the function slope and talk about gradients. While derivatives are single numbers that point in the direction of the steepest descent of a function, gradients take this concept into multiple directions. For example, if you have a 2D functions with variables x and y, the the gradient is a vector; it points in the direction of steepest ascent for x and y. Slides: https://sebastianraschka.com/pdf/lecture-notes/stat453ss21/L05_gradient-descent_slides.pdf ------- This video is part of my Introduction of Deep Learning course. Next video: https://youtu.be/L4xzybIa-bo The complete playlist: https://www.youtube.com/playlist?list=PLTKMiZHVd_2KJtIXOW0zFhFfBaJJilH51 A handy overview page with links to the materials: https://sebastianraschka.com/blog/2021/dl-course.html ------- If you want to be notified about future videos, please consider subscribing to my channel: https://youtube.com/c/SebastianRaschka