Key themes and curated posts

New here? These are some topics I write & speak about. Or navigate via tags or search.

Machine Learning Systems

Exploring ML systems in industry and how they're implemented.


Machine Learning Techniques

Surveys on machine learning methods.


Machine Learning & Engineering

Practices at the intersection of ML and engineering.


Mechanisms for ML and Data Science

Thoughts on what an effective data science process should look like.


Ideas & Opinions

Random ideas and unnecessarily strong opinions.


Writing

Especially in the context of a career in tech and data.


Learning & Career

Practices that worked well for me and general advice.


Summaries & Notes

Summaries and permanent notes, tidied up for public consumption.


Other resources

That are mostly scattered across the internet.

  • applied-ml: Papers and tech blogs on real-world machine learning in industry.
  • ml-surveys: Papers summarizing machine learning advances.
  • applyingml: Papers, guides, and interviews on how to apply ML effectively.
  • ml-design-docs: Template of design docs for machine learning systems.
  • testing-ml: Examples of implementation & behavioral tests for ML code.
  • python-collab-template: Template with tests, type checks, linting, etc.
  • recsys-nlp-graph: Simple recsys and experiment results (built on PyTorch).
  • papermill-mlflow: Experimentation workflow for machine learning.


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