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...
Topic Poll ⢠Feedback ⢠Metrics
28 Feb 2021
  Ā· 
Writing at Work - The Why, What, How Framework
21 Feb 2021
  Ā· 
Feature Stores - A Hierarchy of Needs
14 Feb 2021
  Ā· 
How to Win a Data Hackathon (Hacklytics 2021)
07 Feb 2021
  Ā· 
DataTalksClub - Building an ML System; Behind the Scenes
31 Jan 2021
  Ā· 
Growing and Running Your Data Science Team
24 Jan 2021
  Ā· 
You Don't Really Need Another MOOC
09 Aug 2020
  Ā· 
Unpopular Opinion - Data Scientists Should Be More End-to-End
05 Apr 2020
  Ā· 
Stop Taking Regular Notes; Use a Zettelkasten Instead
27 Feb 2020
  Ā· 
My Journey: From Psych Grad to Leading Data Science at Lazada
26 Jan 2019
  Ā· 
Data Science and Agile (What works, and what doesn't)
23 Aug 2020
  Ā· 
Embrace Beginner's Mind; Avoid The Wrong Way To Be An Expert
09 Jul 2020
  Ā· 
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+ āļø)
ml-surveys
: Papers
summarizing machine learning advances (600+ ā)
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