b7leung/MLE-Flashcards

What this is

A personal collection of 250+ digital flashcards covering machine learning topics, built by an ML researcher for their own study and interview prep. The author shares it publicly so others can use it too.

What's inside

The cards span a wide range: computer science, classical machine learning, modern deep learning, 2D and 3D computer vision, natural language processing, reinforcement learning, and generative models. The README includes three screenshots showing example cards, but doesn't describe their exact content.

Who it's for

The cards assume you already know ML well — they use technical terminology freely. The author suggests:

• If you have a solid ML background: use the cards as-is to review and fill gaps.
• If you're newer to ML: the cards give a good overview of what exists, but you should also use dedicated learning materials (the README links several, like Stanford's CS231n course, a GenAI handbook, a YouTube lecture playlist, Full Stack Deep Learning, and Chip Huyen's ML interviews book).

Caveats from the author

• Some topics are covered more thoroughly or accurately than others.
• The field changes fast, so this isn't meant to be a definitive resource.
• There may be errors or omissions — the author invites feedback.

History

• May 2025: Added cards on reinforcement learning, NeRFs (neural radiance fields), gaussian splatting, generative models, large language models, and vision-language models. Switched the format to PowerPoint for better equation editing.
• July 2022: Initial set of flashcards created.

Bottom line

A free, self-made flashcard deck for reviewing ML concepts — useful for brushing up or interview prep, but best paired with structured courses if you're still learning the basics.