👋 Hi, I'm Eugene Yan

I work at the intersection of machine learning & product to build pragmatic, customer-facing ML systems. Currently an Applied Scientist at Amazon. Outside of work, I also...

• Write & speak about effective data science, data/ML systems, and career growth.
• Teach a free email course to help data scientists be more effective.
• Send a weekly newsletter about effective data science, machine learning, and career.

Get Updates

Topic Poll • Feedback • Metrics

---

• 28 Feb 2021  ·  Writing at Work - The Why, What, How Framework
• 21 Feb 2021  ·  Feature Stores - A Hierarchy of Needs
• 14 Feb 2021  ·  How to Win a Data Hackathon (Hacklytics 2021)
• 07 Feb 2021  ·  DataTalksClub - Building an ML System; Behind the Scenes
• 31 Jan 2021  ·  Growing and Running Your Data Science Team

• 24 Jan 2021  ·  You Don't Really Need Another MOOC
• 09 Aug 2020  ·  Unpopular Opinion - Data Scientists Should Be More End-to-End
• 05 Apr 2020  ·  Stop Taking Regular Notes; Use a Zettelkasten Instead
• 27 Feb 2020  ·  My Journey: From Psych Grad to Leading Data Science at Lazada
• 26 Jan 2019  ·  Data Science and Agile (What works, and what doesn't)

• 23 Aug 2020  ·  Embrace Beginner's Mind; Avoid The Wrong Way To Be An Expert
• 09 Jul 2020  ·  The 85% Rule - When Giving It Your 100% Gets You Less than 85%

View all writing (104 and counting...)

---

• 🚀 email-course: How to be effective at data science & machine learning
• 📚 applied-ml: Papers on real-world machine learning (4,500+ ⭐️)
• 📋 ml-surveys: Papers summarizing machine learning advances (600+ ⭐)
• 🐍 python-collab-template: Template with tests, type checks, linting, etc.
• 🔍 testing-ml: Example tests for machine learning systems
• 🧪 papermill-mlflow: Experimentation workflow for machine learning
• 🛒 recsys-nlp-graph: Simple Recsys and experiment results
• 🎓 omscs-faq: Georgia Tech Online Master's of Science in Computer Science
• 🧬 teardowns: Surveys & deep dives of data/machine learning systems