data science – Andrew Fairless, Ph.D.

What I Read: history, tidyverse

By Andrew Fairless on May 13, 2025February 2, 2025

https://hadley.github.io/25-tidyverse-history A personal history of the tidyverseHadley WickhamJanuary 28, 2025 “I’ll explore the defining features that make the tidyverse unique, highlight the contributions that I’m most proud of, and examineContinue readingWhat I Read: history, tidyverse

What I Read: Command-line Tools, Faster

By Andrew Fairless on September 10, 2024June 29, 2024

https://adamdrake.com/command-line-tools-can-be-235x-faster-than-your-hadoop-cluster.html Command-line Tools can be 235x Faster than your Hadoop ClusterAdam Drake “One especially under-used approach for data processing is using standard shell tools and commands. The benefits of thisContinue readingWhat I Read: Command-line Tools, Faster

What I Read: Scaling to Multi-Terabyte Datasets

By Andrew Fairless on September 9, 2024June 29, 2024

Lessons Learned from Scaling to Multi-Terabyte Datasets v2thegreat, AliLessons Learned from Scaling to Multi-Terabyte DatasetsJune 19, 2024 “This post is meant to guide you through some of the lessons I’ve learnedContinue readingWhat I Read: Scaling to Multi-Terabyte Datasets

What I Read: notebooks, McDonalds of code

By Andrew Fairless on September 5, 2024June 29, 2024

https://yobibyte.github.io/notebooks.html notebooks are McDonalds of codeVitaly Kurin “I later saw the extensive use of notebooks everywhere, even in production, and I don’t laugh anymore. I’m scared and sad.”

What I Read: Cookiecutter Data Science V2

By Andrew Fairless on August 22, 2024June 4, 2024

https://drivendata.co/blog/ccds-v2 Cookiecutter Data Science V2by Peter Bull, Jay Qi, Chris KucharczykWed 22 May 2024 “…in the past 5 years, a lot has changed in data science tooling and MLOps. CookiecutterContinue readingWhat I Read: Cookiecutter Data Science V2

What I Read: anti-patterns, data reuse

By Andrew Fairless on July 10, 2024May 6, 2024

https://www.milesmcbain.com/posts/data-analysis-reuse Patterns and anti-patterns of data analysis reuseMiles McBainMarch 10, 2024 “When I look at that function signature I hear the screams of matrices being ground to a fine powderContinue readingWhat I Read: anti-patterns, data reuse

What I Read: Data Science, Mostly Dispatch

By Andrew Fairless on July 1, 2024April 23, 2024

https://truetheta.io/concepts/opinions-and-speculations/good-data-science-is-mostly-dispatch Good Data Science is Mostly DispatchDJ RichOctober 27, 2023 “By good data science is mostly dispatch, I mean most of what explains a job well done is the choiceContinue readingWhat I Read: Data Science, Mostly Dispatch

What I Read: Don’t put notebooks into production

By Andrew Fairless on June 27, 2024April 23, 2024

https://martinfowler.com/articles/productize-data-sci-notebooks.html Don’t put data science notebooks into productionDavid Johnston18 November 2020 “…the discussion of how to productionize data science notebooks is missing the point. The goal should be to empowerContinue readingWhat I Read: Don’t put notebooks into production

What I Read: Navigating Data Tensions

By Andrew Fairless on February 28, 2024January 25, 2024

https://dataanalysis.substack.com/p/special-edition-analytics-as-applied Special Edition: Navigating Data Tensions and the Future of Analytics | Lauren BalikOlga Berezovsky and Lauren BalikJan 8, 2024 “…it is now more expensive to acquire new customers, andContinue readingWhat I Read: Navigating Data Tensions

What I Read: Why Most Data Projects Fail

By Andrew Fairless on August 2, 2023June 15, 2023

Why Most Data Projects Fail & How to Avoid It • Jesse Anderson • GOTO 2023GOTO ConferencesJun 14, 2023 “This talk will explore the most common reasons data projects failContinue readingWhat I Read: Why Most Data Projects Fail

Tag: data science