This repository is an educational documentation project, not a runtime application: index.js is a placeholder comment, and the only executable code is a ~70-file Vitest test suite whose purpose is to verify, line-by-line, the code examples embedded in ~60 MDX documentation pages. The docs cover 33 core JavaScript concepts plus a 'Beyond 33' extension of ~29 advanced topics (observer APIs, memory management, WeakMap/WeakSet, IndexedDB, etc.), rendered as a Mintlify site at 33jsconcepts.com. Each test file maps 1:1 to a concept page and references exact source line numbers in the .mdx files, making the tests executable documentation. GitHub Actions CI runs the suite on push/PR against Node LTS.
This is a Chinese-language educational companion to DeepLearning.AI's 'Agentic AI' course by Andrew Ng, maintained by the Datawhale community. The repository is a hybrid learning resource: ~60 translated markdown files across 5 modules (agentic workflow intro, reflection design patterns, tool use, practical building tips, highly autonomous agents) plus executable Jupyter notebooks and supporting Python modules that implement the lab exercises. It is not a production application or service — it is courseware with real, runnable agent code demonstrating current LLM agent patterns.
This repository is not a software application, data pipeline, or research codebase. It is a content-distribution repository for a single educational artifact: a 'VIP cheatsheet' PDF condensing Stanford CME 295 (Transformers & Large Language Models). The repo contains 16 language folders, each holding one PDF and one translated README, plus a root README and an MIT license. There is zero executable code, no tests, no CI/CD, no dependency manifests, and no data processing logic of any kind. It is classified as data_research only by process of elimination — binary data files dominate and there are no application entry points — but in reality it is educational content, a hybrid that fits neither software nor data-engineering categories cleanly.
This repository is primarily a static personal website for author Li Xiaolai, hosting multiple original books and educational resources (e.g., 'Everyone Can Use English', Bitcoin whitepaper translation, TOEFL essay collection) as well as two interactive web applications: a Monte Carlo retirement projection tool and a historical ETF retirement strategy demo. The Monte Carlo tool is a well-crafted client-side financial simulator using Geometric Brownian Motion, Box-Muller transform, and Chart.js, complete with a standalone Node.js test suite. The site is built with docsify-style navigation and deployed via GitHub Actions to Alibaba Cloud OSS. While the content dominates the repository, the Monte Carlo application demonstrates solid engineering practices (modular JS, test coverage, performance-aware Float64Array usage) and is the most reusable software component. The repository is actively maintained (latest commit 2026-04-14, CI/CD active), but the surrounding static content has no build system or dependency management, and the Monte Carlo app relies on CDN-hosted Chart.js and a CORS proxy, posing medium technical drift risk.
This repository is a comprehensive knowledge base and research platform for quantitative finance, primarily focused on Chinese A-share markets. It contains hundreds of blog posts, course materials, and technical articles covering factor investing, machine learning strategies, backtesting frameworks, and data engineering. The codebase includes reusable data pipelines (ParquetUnifiedStorage, CalendarModel), a custom backtesting framework (Moonshot), and numerous factor analysis scripts. It also hosts a sophisticated set of AI-assisted academic research skills (paper writing, review, deep research) defined as Claude skill files. The repository serves as both an educational resource and a personal research lab, with content spanning from beginner Python tutorials to advanced factor construction and model training. While the code is functional and demonstrates solid data engineering patterns, it is tightly coupled to Chinese financial data APIs (Tushare, akshare) and contains hardcoded paths, limiting portability. The repository is actively maintained but shows signs of technical drift in some dependencies and content duplication.
This repository is a collection of front-end code examples (HTML, CSS, JavaScript) created for video tutorials on Bilibili. It contains over 50 standalone projects demonstrating various web techniques such as CSS animations, SVG effects, glassmorphism, parallax scrolling, face recognition, Lottie animations, and interactive physics. The main entry point is a React-based navigation page, but each example is self-contained in its own folder. The code is primarily educational and not intended for production use. Dependencies are outdated (React 17, Babel 7.12) and there is no testing or CI/CD. While some components exhibit creative use of web APIs, the overall codebase is boilerplate-heavy and tightly coupled to its tutorial context, limiting reusability.