Materials

Book

Dive into Deep Learning by Zhang, Aston, Zachary C. Lipton, Mu Li, and Alexander J. Smola: a great online book that covers most of the content of our course (with code) and also provides the preliminary background for Deep Learning. It also has a free pdf version and you can also buy a hard copy on Amazon.

Math and ML Background

• Stanford’s preliminary docs in Linear Algebra and Calculus.
• Machine Learning Mastery: Great resource for anything ML, including a page on Linear Algebra for ML.
• The Hundred-Page Machine Learning Book: Great crash course in ML (the title says it all).

Additional Course Materials

• Latex Tutorial: you’ll need Latex for most of the assigments! I suggets you use Overleaf and an latex template from a sceintific journal (like this one).
• Pytorch Tutorial: In case you need another resource.