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...
03 Nov 2024
  ·  39 Lessons on Building ML Systems, Scaling, Execution, and More
27 Oct 2024
  ·  AlignEval: Building an App to Make Evals Easy, Fun, and Automated
22 Sep 2024
  ·  Weights & Biases LLM-Evaluator Hackathon - Hackathon Judge
08 Sep 2024
  ·  Building the Same App Using Various Web Frameworks
18 Aug 2024
  ·  Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge)
07 Jul 2024
  ·  How to Interview and Hire ML/AI Engineers
27 Jun 2024
  ·  AIE World's Fair 2024 Keynote - What We Learned from a Year of LLMs
31 May 2024
  ·  Netflix PRS 2024 - Applying LLMs to Recommendation Experiences
26 May 2024
  ·  Prompting Fundamentals and How to Apply them Effectively
12 May 2024
  ·  What We've Learned From A Year of Building with LLMs
12 May 2024
  ·  What We've Learned From A Year of Building with LLMs
30 Jul 2023
  ·  Patterns for Building LLM-based Systems & Products
11 Jun 2023
  ·  Obsidian-Copilot: An Assistant for Writing & Reflecting
21 May 2023
  ·  Some Intuition on Attention and the Transformer
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
27 Jun 2024
  ·  AIE World's Fair 2024 Keynote - What We Learned from a Year of LLMs
31 May 2024
  ·  Netflix PRS 2024 - Applying LLMs to Recommendation Experiences
09 Oct 2023
  ·  AI Engineer Summit 2023 Keynote - Building Blocks for LLM Systems
23 Sep 2022
  ·  RecSys 2022 Keynote - Is the Juice Worth the Squeeze?
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%
192 posts, 29 talks, 16 prototypes, 381,436 words, and countless hours.
• AlignEval: An App to Make Evals Easy, Fun, and Semi-Automated
• AI Coach: Talk to Tara, an AI Coach, anytime at +1 (206) 558 8782
• Obsidian-Copilot: A Prototype Assistant for Writing and Reflecting
• Raspberry-LLM: Dr. Seuss headlines, HackerNews trolls, etc.
• ApplyingML.com: Ghost knowledge of applying ML effectively
• RecSys in PyTorch: Baselines + improvements via Graphs & NLP
• Image Classification: Transfer learning via Keras and Theano
• Title Classification: Getting Amazon data, modeling, building a UI
applied-llms.org
:
Practical lessons from a year of building with LLMs
applyingml.com
:
Papers, guides, and interviews on how to apply ML effectively
applied-ml
:
Papers on real-world machine learning systems in industry
open-llms
:
Open large language models available for commercial use
llm-reading-list
:
Language modeling reading list (to start a paper club)
ml-design-docs
:
Template of design docs for machine learning systems
python-collab-template
:
Template with tests, type checks, linting, etc.
papermill-mlflow
:
Experimentation workflow for machine learning
1-on-1s
:
Questions to ask during 1-on-1s, from my time as a manager
omscs-faq
:
Georgia Tech Online Master's of Science in Computer Science
teardowns
:
Surveys & deep dives of data/machine learning systems