🔖 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.


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

Learning & Career

Practices that worked well for me and general advice.


Random philosophical ideas and thoughts.

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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