I design, build, and operate machine learning systems that serve customers at scale. Currently, I'm a Senior Applied Scientist at Amazon. 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 with practitioners and a weekly LLM reading group.
• Send a newsletter on data, ML, and what I'm learning to 6,100+ subscribers.

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• 05 Nov 2023  ·  Out-of-Domain Finetuning to Bootstrap Hallucination Detection

• 15 Oct 2023  ·  Reflections on AI Engineer Summit 2023

• 09 Oct 2023  ·  AI Engineer Summit - Building Blocks for LLM Systems & Products

• 03 Sep 2023  ·  Evaluation & Hallucination Detection for Abstractive Summaries

• 13 Aug 2023  ·  How to Match LLM Patterns to Problems

• 30 Jul 2023  ·  Patterns for Building LLM-based Systems & Products

• 09 Apr 2023  ·  Experimenting with LLMs to Research, Reflect, and Plan

• 14 Aug 2022  ·  Simplicity is An Advantage but Sadly Complexity Sells Better

• 31 Jul 2022  ·  Uncommon Uses of Python in Commonly Used Libraries

• 12 Jun 2022  ·  Design Patterns in Machine Learning Code and Systems

• 19 Sep 2021  ·  The First Rule of Machine Learning: Start without Machine Learning

• 27 Jun 2021  ·  System Design for Recommendations and Search

• 28 Feb 2021  ·  How to Write Better with The Why, What, How Framework

• 21 Feb 2021  ·  Feature Stores: A Hierarchy of Needs

• 10 Jan 2021  ·  Real-time Machine Learning For Recommendations

• 09 Aug 2020  ·  Unpopular Opinion: Data Scientists Should be More End-to-End

• 05 Apr 2020  ·  Stop Taking Regular Notes; Use a Zettelkasten Instead

• 09 Oct 2023  ·  AI Engineer Summit - Building Blocks for LLM Systems & Products

• 23 Sep 2022  ·  RecSys 2022 Keynote - Is the Juice Worth the Squeeze?

• 15 Sep 2021  ·  MLOps Community - System Design for RecSys & Search

• 17 Jan 2021  ·  DataTalksClub - The Importance Of Writing In A Tech Career

• 03 Oct 2019  ·  OLX Prod Tech 2019 Keynote - Asia's Tech Giants & SuperApps

• 04 Sep 2022  ·  Writing Robust Tests for Data & Machine Learning Pipelines

• 02 May 2021  ·  The Metagame of Applying Machine Learning

• 28 Feb 2021  ·  How to Write Better with The Why, What, How Framework

• 02 Aug 2020  ·  What I Did Not Learn About Writing In School

• 09 Jul 2020  ·  The 85% Rule: When Giving It Your 100% Gets You Less than 85%

175 posts, 26 talks, 13 prototypes, 328,111 words, and countless hours.

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• • Obsidian-Copilot: A Prototype Assistant for Writing and Reflecting

• • LLM UXs: Interacting with LLMs with Minimal Chat

• • Raspberry-LLM: Dr. Seuss headlines, HackerNews trolls, etc.

• • LLM Experiments: LLM assistants, retrieval, and Discord

• • ApplyingML.com: Ghost knowledge of applying ML effectively

• • RecSys in PyTorch: Baselines + improvements via Graphs & NLP

• • Image Search: Image embeddings + cosine similarity

• • Image Classification: Transfer learning via Keras and Theano

• • Title Classification: Getting Amazon data, modeling, building a UI

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  applied-ml: Papers on real-world machine learning systems in industry

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  applyingml: Papers, guides, and interviews on how to apply ML effectively

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  open-llms: Open large language models available for commercial use

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  ml-design-docs: Template of design docs for machine learning systems

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  testing-ml: Example tests for machine learning systems

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  python-collab-template: Template with tests, type checks, linting, etc.

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  papermill-mlflow: Experimentation workflow for machine learning

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  1-on-1s: Questions to ask during 1-on-1s, from my time as a manager

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  omscs-faq: Georgia Tech Online Master's of Science in Computer Science

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  teardowns: Surveys & deep dives of data/machine learning systems