What it does This is a living bookmark collection for machine learning resources, maintained in Russian and organized like a syllabus. It catalogs textbooks, MOOCs, interview prep, toy datasets, and community links across topic pages (NLP, neural nets, linear algebra, R, Python tooling, etc.). Think of it as a syllabus someone else keeps current so you don’t have to hunt.

The interesting bit The curation has a distinctly academic Russian flavor: Vorontsov’s lecture notes, prep reading for Yandex’s SHAD graduate program, and classic texts like Elements of Statistical Learning alongside their Russian translations. It’s not just “another awesome-list” — it reads like a reading list from a Moscow CS faculty lounge.

Key highlights

• ~40+ textbooks in the “ML specialist library” section, many with direct PDF or free links
• Topic-specific sub-pages (Big Data, Dataviz, LaTeX, algorithms, probability)
• Curated extras: data-science interview questions, competition calendars, Docker images for DS projects, a Trello board of verified materials
• Explicitly “constantly updated” — the README’s own claim, for what that’s worth
• Strong coverage of foundational math (linear algebra, statistics) rather than just framework tutorials

Caveats

• The README is a flat link dump with minimal annotation; you’ll do your own triage
• Some links are to external gists, Dropbox folders, and PDF archives — durability not guaranteed
• “Constantly updated” is the author’s claim; last substantial update timing is unclear from the README alone

Verdict Worth a bookmark if you’re Russian-speaking, self-teaching ML from mathematical foundations, or applying to SHAD. English-only developers already drowning in “awesome-ml” lists can probably skip it.