eugeneyan

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

📋 A list of open LLMs available for commercial use.

📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.

📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)

🤖 A prototype assistant for writing and thinking

🌱 1-on-1 questions and resources from my time as a manager.

📰 Building News Agents to Summarize News with MCP, Q, and tmux

🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.

Notes from the Latent Space paper club. Follow along or start your own!

📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.

🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.

Semantic IDs: How to train an LLM-Recommender Hybrid with steerability and reasoning on recommendations.

🛒 Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.

Sample repository demonstrating how to use FastAPI to serve HTML web apps.