Today's brand-new, epic 40-minute YouTube tutorial ties together the preceding 27 Calculus videos to enable us to perform Machine Learning from first principles and fit a line to data points.

To make learning interactive and intuitive, this video focuses on hands-on code demos featuring PyTorch, the popular Python library for Automatic Differentiation.

If you're familiar with differential calculus but not machine learning, this video will make clear for you how ML works. If you're not familiar with differential calculus, the preceding videos in my "Calculus for Machine Learning" course will provide you with all of the foundational theory you need for ML.

We publish a new video from my "Calculus for Machine Learning" course to YouTube every Wednesday. Playlist is here.

More detail about my broader "ML Foundations" curriculum and all of the associated open-source code is available in GitHub here.