Uploaded February 2021 | Updated September 2026, 2 weeks ago

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Sebastian's books: sebastianraschka.com/books

Now that we understand computation graphs and saw how PyTorch can differentiate computations automatically, let's use it to train the adaptive linear neuron that we introduced in lecture 5 more conveniently.

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L06_pytorch_slides.pdf
Code: github.com/rasbt/stat453-deep-learning-ss21/blob/main/L06/code/adaline-with-autograd.ipynb

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This video is part of my Introduction of Deep Learning course.

Next video: youtu.be/klc79sZ1yVc

The complete playlist: youtube.com/playlist?list=PLTKMiZHVd_2KJtIXOW0zFhFfBaJJilH51

A handy overview page with links to the materials: sebastianraschka.com/blog/2021/dl-course.html

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