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πŸ‘‹ Hi, I'm Eugene Yan

I design, build, and operate machine learning systems that serve customers at scale. Currently, I'm a Senior Applied Scientist at Amazon helping users read more, and get more out of reading. Outside of work, I also...

  • Write, speak, and prototype on ideas in machine learning, RecSys, and LLMs.
  • Curate papers, guides, and interviews on applying machine learning effectively.
  • Host monthly ML meetups and a weekly LLM reading group with practitioners.
  • Send a newsletter about data, ML, and what I'm learning to 6,300+ subscribers.
  • In 2024 I'm learning: Synthetic data, application evals, and scaling ML teams.
  • Fun fact: I don't use the QWERTY keyboard (I use Dvorak instead).

πŸ“ Recent Writing

View the archives (180 posts) @ eugeneyan.com.


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Eugene Yan's Projects

1-on-1s icon 1-on-1s

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

applied-ml icon applied-ml

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

applyingml icon applyingml

πŸ“Œ Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comβ€”the ghost knowledge of machine learning.

deep-rl icon deep-rl

Repository for deep reinforcement learning with OpenAI

discord-llm icon discord-llm

Experimenting with LLMs to Research, Reflect, and Plan (LLM assistants, retrieval, and Discord integration)

dksg-home icon dksg-home

Sharing my R script used in the DKSG DataLearn for home

evals icon evals

Evals is a framework for evaluating OpenAI models and an open-source registry of benchmarks.

fastapi-html icon fastapi-html

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

islr-labs icon islr-labs

Notes and exercise attempts for "An Introduction to Statistical Learning"

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