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Study Notes

A structured knowledge base with an interactive web interface. Built for efficient learning, quick reference, and interview preparation.

View Online: haoweichan.github.io/study-notes

What's Inside

📚 Knowledge Base — Notes on Algorithms, System Design, Machine Learning (AdTech focus), and Agentic AI.

🧠 Active Learning — 120+ Flashcards and Quizzes with real-time search, category filtering, dark mode, bookmarks, and spaced repetition.

⚡ Clean Architecture — Markdown-first notes with auto-extracted flashcards/quizzes, automated linting, and GitHub Pages deployment via React/Vite.

Repository Structure

study-notes/
├── web/                     # React + Vite Web Application
│   ├── src/                 # Frontend source code
│   └── public/              # Static assets
├── docs/                    # Deployment target (GitHub Pages)
│   ├── artifacts/           # Auto-generated JSON data
│   └── notes/               # Copied markdown content
├── notes/                   # Source Markdown notes
│   ├── algorithm/           # Algorithms & data structures
│   ├── devops/              # DevOps & infrastructure
│   ├── system-design/       # System architecture
│   ├── machine-learning/    # ML (AdTech, RecSys)
│   ├── leetcode/            # Coding problem solutions
│   └── agentic/             # AI Agents, RAG, GenAI
├── templates/               # Note templates
├── scripts/                 # Automation scripts
│   ├── new_note.sh          # Create new notes
│   ├── deploy_web.sh        # Build & Deploy script
│   ├── export_notes_index.py # Index notes for WebUI
│   └── ...
└── .github/workflows/       # CI/CD for linting

Usage

Creating New Notes

Use the provided helper script to create new notes from the template:

./scripts/new_note.sh "Title of note" <category> [slug]

Available Categories:

  • algorithm — Algorithms & data structures
  • devops — Infrastructure & DevOps
  • system-design — System architecture
  • machine-learning — ML & AI
  • leetcode — Coding problems
  • agentic — AI agents & automation

Examples:

./scripts/new_note.sh "Binary Search Tree" algorithm
./scripts/new_note.sh "Design Real-Time Bidding" system-design
./scripts/new_note.sh "RAG Architectures" agentic

Adding Content

Flashcards:

- What is the time complexity of binary search? ::: O(log n)

Quizzes:

## Quizzes
Q: Question?
Options:
- A) Option 1
- B) Option 2
Answers: A
Explanation: ...

Note Format

All notes should follow this structure:

  • Location: notes/{category}/short-slug.md
  • Frontmatter: Required fields are title, date, and category
  • Sections: Include Summary, Details, Flashcards, Quizzes

Local Development & Deployment

1. Install Dependencies

# Python dependencies for generation scripts
pip install python-frontmatter

# Web dependencies
cd web
npm install

2. Deploy Locally (Build & Copy)

# Builds the React app and generates artifacts into docs/
./scripts/deploy_web.sh

3. Serve Locally

# Verify the build
python -m http.server 8000 -d docs

Linting

The repository includes multiple layers of linting:

  1. GitHub Actions: Run linting on all pull requests and pushes
  2. Manual checking: Run npx remark . and npx markdownlint "**/*.md" locally