Maths, CS and AI Compendium
Details
- External ID
- 47036063
- Source
- HN
- Company
- —
- Product
- CS
- Website domain
- github.com
- Launched
- Feb. 16, 2026
- Cohort
- —
- Upvotes
- 88
- Upvotes percentile
- 0.8800539083557951
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:25 p.m.
- Updated at
- Sept. 7, 2026, 9:25 p.m.
Description
Hey HN, I don’t know who else has the same issue, but:Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI.Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts.In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing.This is an open & unconventional textbook covering maths, computing, and artificial intelligence from the ground up. For curious practitioners seeking deeper understanding, not just survive an exam/interview.To ambitious students, an early careers or experts in adjacent fields looking to become cracked AI research engineers or progress to PhD, dig in and let me know your thoughts.
Enrichment
- Theme
- ai-powered learning and skills training
- Vertical
- Education
- Function
- —
- Audience
- B2C
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- maths cs and ai compendium
- Manually corrected
- False
Could you build this?
No The core product is not software infrastructure but deep, verified mathematical and computer science educational content accumulated over years of specialized academic study and practice.
What it would actually take: Producing this compendium requires deep domain expertise across linear algebra, calculus, algorithms, and deep learning architectures, combined with pedagogical design and LaTeX typesetting. While hosting it on a static documentation site (e.g., VitePress) is trivial, the primary effort is original technical research, derivation verification, and creating intuitive explanatory diagrams.
Discussion
20 comments analyzed.
Competitors mentioned: Gemini (quiz/test mode for learning), GitBook (for hosting study websites), Textbooks (paired with AI for learning)
Concerns raised: Coding exercises lack feedback, Limited depth on sub-topics
Feature requests: Add authoritative resources for further deep dives, Provide feedback for coding exercises, Generate static website hosting
Competitors
Other products that read as similar to this one — 198 launches clear the similarity bar, closest 8 shown.
Attention rank: #27 of 199 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 108 days after the earliest competitor.
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- Social and context-aware AI platform to do math · hn · 2026-07-05 · 5 upvotes · similarity 0.44
- MathPaperAI · ph · 2026-09-18 · 3 upvotes · similarity 0.44
- Book · ph · 2026-09-29 · 1 upvotes · similarity 0.44