250+ flashcards I made as an exercise & reference for myself, after from years of ML research, coursework, & independent study. Hopefully other people can benefit from them as well, for study or interview prep!
Topics covered includes: computer science, classical ML, modern deep learning, 2D/3D computer vision, NLP, reinforcement learning, generative models.
The PDFs in this repo are mostly for convenience. Check out these presentation slide links for the most up to date and animated Q&A versions, with additional links in the speaker notes:
- 1 Computer Science Slides
- 2 Machine Learning General Slides
- 3 Fundamentals for Computer Vision & Deep Learning Slides
- 4 Selected Topics in Computer Vision & Deep Learning Slides
These flashcards generally assume a good foundation in these topics, and a lot of technical terminology is used. I think your approach might be different depending on your current experience:
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Already have a good foundation in ML: you can probably use them as-is to review and fill in any missing knowledge gaps
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Newer to ML, this may provide a good overview of what is out there, and I'd suggest also refering to other materials focused on education & learning (see "additional links" below)
Note that some topics are covered more comprehensively/accurately than others -- and because the field is constantly changing, this is not meant to be a definitive resource. There may be errors in these slides, or things that I've missed. If so, feel free let me know!
- May 2025 -- Updated with topics in RL, NeRFs, gaussian splatting, generative models, LLMs, and VLMs. Switched to powerpoint due to better equation editing.
- July 2022 -- Initial set of flashcards.
