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interestedGitHub

GitHub - mawady/awesome-computer-vision-resources: A structured learning reference for computer vision: from image fundamentals to research frontiers

A structured learning reference for computer vision: from image fundamentals to research frontiers - mawady/awesome-computer-vision-resources

https://github.com/mawady/awesome-computer-vision-resources

interestedplato.stanford.edu

Stanford Encyclopedia of Philosophy

https://plato.stanford.edu/

interestedarxiv.org

arXiv.org e-Print archive

https://arxiv.org/

interestedMIT OpenCourseWare

MIT OpenCourseWare | Free Online Course Materials

MIT OpenCourseWare is a web based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity

https://ocw.mit.edu/

interestedXiyang Hu

Xiyang Hu | resources

A curated collection of high-quality resources for students and researchers. While many of these materials are written by computer science scholars (👏 to their open-source spirit), the insights are broadly applicable across disciplines.

https://xiyanghu.github.io/resources/

interestedGenerative AI

AI & ChatGPT Courses

https://www.linkedin.com/feed/update/urn:li:groupPost:6731624-7458105740260577280/?utm_source=social_share_send&utm_medium=ios_app&rcm=ACoAAAjAjYsBU8DxE_HE298uJ8uo6Z6DuXaH3bo

interestedvinija.ai

Vinija's Notes • CS224n: Natural Language Processing with Deep Learning

Vinija's detailed AI Notes

https://vinija.ai/nlp/

interestedStanford

CME Stanford

https://stanford.edu/~shervine/teaching/cme-106/

interestedTuring

Turing Test

https://developers.turing.com/dashboard/turing_test

interestedNotion

LLM

https://www.notion.so/Transformers-LLMs-UCL-6ae7cd3c0c8b4835aa2e7d4372568714

interestedSpacy

Advanced NLP with Spacy

https://course.spacy.io/en/

interestedMIT OpenCourseWare

Introduction to Algorithms | Electrical Engineering and Computer Science | MIT OpenCourseWare

This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems.

https://ocw.mit.edu/courses/6-006-introduction-to-algorithms-spring-2020/