TDD or not TDD: How to write tests in Data Science
Why anti-OOP content is wrong?
[Interesting content] Adam Tornhill - A Crystal Ball to Prioritize Technical Debt
MLOps Live with neptune.ai - Writing clean, production-level ML code
Refactoring the Titanic
What's still wrong with MLOps?
Data Science code quality hierarchy of needs
How python programmers save the environment (by making python run faster)?
Can you version control Jupyter notebooks?
How did I change my mind about dataclasses in ML projects?
Slides for my talk at PyData London 2022
User Comments on: "How can a Data Scientist refactor Jupyter notebooks towards production-quality code?"
Industrial Scale Text Classification
Clean Architecture in Data Science (Part 1)
Getting Data Scientists to Write Better Code 🔥 with Laszlo Sragner
Documentation vs Documentation in Data Science
AI and COVID: A lesson of ML product design
Article Review: Rendezvous Architecture for Data Science in Production by Jan Teichmann
Article Review: Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology by Mercedes-Benz AG and TU Berlin
Article Review: Machine Learning operations maturity model by Microsoft
Article Review: MLOps: Continuous delivery and automation pipelines in machine learning by Google
Article Review: Rules of Machine Learning: Best Practices for ML Engineering by Google
Article Review: The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction by Google
Article Review: Hidden Technical Debt in Machine Learning Systems by Google
Article Review: Machine Learning: The High-Interest Credit Card of Technical Debt by Google
3 Ways Domain Data Models help Data Science Projects
Unpopular Opinion: “Data-centric AI” is a straw man argument
How Data Scientists cheat in Wordle?
5 Minimalist Tips for Data Scientists to reduce frustration while working with Pandas
Causes of Machine Learning’s productivity problem
3 paradoxes of rule-based Machine Learning systems
Unpopular Opinion: Agile is not only suitable for Data Science projects, but it is the only way to run one
Simple trick to optimise code and maintain readability in a compute heavy application
Causes of Machine Learning’s productivity problem: Process
Causes of Machine Learning’s productivity problem: Metrics
Causes of Machine Learning's productivity problem: Technology
Causes of Machine Learning's productivity problem: Teams
Causes of Machine Learning’s productivity problem: Strategy