MLE-Flashcards
# Machine Learning Flashcards 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**.    # Intended Scope and Audience These flashcards generally assume a good foundation in these topics, and a lot of technical terminology is used. Potential approaches may differ depending on your current experience: * Already have a __good foundation in ML__: you can probably use them __as-is to review__ and fill in any missing knowledge gaps * __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! # Changelog * **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. # Additional Links & Resources * http://cs231n.stanford.edu/ * https://genai-handbook.github.io/ * https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ * https://fullstackdeeplearning.com/spring2021/ * https://huyenchip.com/ml-interviews-book/