This repository is an educational reference and study guide for system design interviews. It is not a deployable application or data pipeline. It provides a structured index of system design topics, solution sketches for common design problems (e.g., pastebin, Twitter, web crawler), and Python code snippets illustrating key patterns like LRU caching, hash tables, BFS on social graphs, and MapReduce. The material is oriented toward preparing engineers for technical interviews, with back-of-the-envelope calculations, REST API designs, and scalability discussions. The code examples are minimal, self-contained, and demonstrate fundamental computer science patterns, but are not production-grade software. The repository also includes Anki flashcard decks for spaced repetition.
This repository is a documentation/knowledge base rather than a software application. Its sole content asset is a single comprehensive README.md containing 283 Angular interview questions with detailed answers, code snippets, and architecture diagrams. Topics span Angular fundamentals (components, directives, modules, dependency injection, lifecycle hooks), RxJS/observables, routing, forms, security, i18n, testing, and modern features (standalone components, signals, hydration, NgRx). The only automation is a GitHub Actions workflow that converts README.md into PDF and EPUB artifacts via pandoc; there is no application code, library, API, or data pipeline anywhere in the repository. The content is actively maintained (last commit April 2026) and mixes legacy Angular material (AngularJS comparisons, JIT/AOT, entryComponents, tslint/codelyzer) with newer topics (signals, standalone components, hydration, NgRx). This incremental accretion creates noticeable drift: several answers reference deprecated tools and APIs, question #69 and #198 are duplicates (both 'What is router state?'), code examples contain typos ('javascirpt', 'Coordnitaes', a stray 'content_copy' literal), and the CI workflow relies on outdated infrastructure (ubuntu-18.04, actions/checkout@v2, upload-artifact@master). Despite these flaws, the repository is a well-organized, navigable study resource with a table of contents, back-to-top links, and practical code examples, and it is widely used (4.9k stars, 2.2k forks).
This repository is a comprehensive, curated collection of cybersecurity study plans covering 20+ specialized domains such as application security, cloud security (AWS/Azure/GCP), DevSecOps, threat modeling, GRC, GenAI security, and more. It is not a software application or data research project; rather, it is a knowledge base of structured markdown roadmaps designed to guide learners and professionals through role-specific cybersecurity skill development. The plans reference up-to-date frameworks (OWASP Top 10:2025, NIST CSF 2.0, EU AI Act), include curated resources (books, videos, courses, certifications), and are consistently maintained. The repository has high community engagement (5k+ stars) and remains actively updated, though it contains no executable code, data pipelines, or notebooks.
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 a Chinese translation and adaptation of the 'CCNA in 60 Days' study guide, organized as an mdBook static site with a companion Tauri desktop application. The primary content consists of 60 daily lessons covering Cisco CCNA exam topics (routing, switching, security, WAN, etc.), each with theory, configuration examples, review questions, and hands-on labs. The desktop app (src-tauri/) provides offline reading, bookmarking, reading progress tracking, and an LLM assistant (Anthropic Claude) for answering questions about the material. The project is hybrid: the vast majority of the repository is documentation, but it also includes a functional application wrapper with CI/CD. While the educational content is thorough and well-structured, the application components are minimal and tightly coupled to the mdBook ecosystem. The repository appears to have been abandoned (last commit with a future date indicates likely clock skew or repository corruption; no recent activity).
This repository is a crowdsourced collection of quiz questions and answers for LinkedIn skill assessments across dozens of technical domains (programming languages, frameworks, cloud platforms, design tools, etc.). The data is organized into topic directories, each containing a markdown file with multiple-choice questions, correct answers marked, and occasional reference links. Translations into multiple languages are provided. The repository includes a Python script (translate.py) for automated translation using Google Translate. The primary purpose is as a study aid for job seekers and interview preparation. The content is static and not actively maintained, leading to potential inaccuracies for current software versions. It is not an application or data pipeline but rather a curated knowledge base.