eugeneyan/applied-ml ? reverse-engineered prompt

Build me a simple, clean resource hub for applied machine learning in production. I want it to feel like a curated library of papers, engineering blogs, and articles from real companies, grouped by topics like data quality, data engineering, recommendation, search, NLP, computer vision, reinforcement learning, MLOps, team structure, and failure stories.

Each item should show the title, company, year, and link out to the original source. Make it easy to browse by category, search across everything, and filter by company or year. A small summary or short description for each entry would be great when available, but the main goal is a neat, readable directory that helps people quickly learn how companies actually built ML systems in practice.

Please make it easy to maintain and contribute to later, since this kind of list will keep growing. If the content already exists in a markdown README, reuse that as the source instead of rewriting everything by hand. Keep the design lightweight and fast. You can look up current docs online if needed.