Eugene Yan
102 articles archived · Visit source ↗ · RSS
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Eugene Yan research 39mo ago
LLM-powered Biographies
Asking LLMs to generate biographies to get a sense of how they memorize and regurgitate.
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How to Write Data Labeling/Annotation Guidelines
Writing good instructions to achieve high precision and throughput.
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Mechanisms for Effective Machine Learning Projects
Pilot & copilot, literature review, methodology review, and timeboxing.
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Goodbye Roam Research, Hello Obsidian
How to migrate and sync notes & images across devices
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What To Do If Dependency Teams Can’t Help
Seeking first to understand, earning trust, and preparing for away team work.
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2022 in Review & 2023 Goals
Travelled, wrote, and learned a lot, L5 -> L6, gave a keynote at RecSyS, and started a meetup.
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RecSys 2022: Recap, Favorite Papers, and Lessons
My three favorite papers, 17 paper summaries, and ML and non-ML lessons.
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Writing Robust Tests for Data & Machine Learning Pipelines
Or why I should write fewer integration tests.
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Simplicity is An Advantage but Sadly Complexity Sells Better
Pushing back on the cult of complexity.
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Uncommon Uses of Python in Commonly Used Libraries
Some off-the-beaten uses of Python learned from reading libraries.
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Why You Should Write Weekly 15-5s
15 minutes a week to document your work, increase visibility, and earn trust.
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Design Patterns in Machine Learning Code and Systems
Understanding and spotting patterns to use code and components as intended.
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What I Wish I Knew About Onboarding Effectively
Mindset, 100-day plan, and balancing learning and taking action to earn trust.
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Bandits for Recommender Systems
Industry examples, exploration strategies, warm-starting, off-policy evaluation, and more.
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Traversing High-Level Intent and Low-Level Requirements
How they differ and why they work better in different situations.
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Data Science Project Quick-Start
Hard-won lessons on how to start data science projects effectively.
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Red Flags to Look Out for When Joining a Data Team
What to consider for in terms of data, roadmap, role, manager, tooling, etc.
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How to Keep Learning about Machine Learning
Beyond getting that starting role, how does one continue growing in the field?
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2021 Year in Review
Met most of my goals, adopted a puppy, and built ApplyingML.com.
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Informal Mentors Grew into ApplyingML.com!
More than two dozen interviews with ML Practitioners sharing their stories and advice
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RecSys 2021 - Papers and Talks to Chew on
Simple baselines, ideas, tech stacks, and packages to try.
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Influencing without Authority for Data Scientists
Show them the data, the Socratic method, earning trust, and more.
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The Metagame of Applying Machine Learning
How to go from knowing machine learning to applying it at work to drive impact.
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Planning Your Career: Values and Superpowers
What do you deeply care about? What do you excel at? Build a career out of that.
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