I find it genuinely interesting to see where things I write end up. Not in a “look at my press coverage” way, but more anthropologically: what resonates? What travels? What gets picked up by places I’d never expect?
This page tracks external references to posts on this site. Some I’ll editorialize on, most I won’t. Organized by what they linked to.
Some of these are old links to my old domain (willmcginnis dot com) which is currently being squatted by a malicious chinese site that you should not actually go to, but I’d like to get back. In the meantime I’ve been trying to contact these authors to have them update the links to this domain so they work for their readers. If you are one such author, please update.
Category Encoders Posts
The category-encoders library started as a companion to a blog post I wrote in 2015. A decade later, the posts are still cited in the package documentation itself, which is a nice bit of permanence. These posts have had surprisingly long legs in the ML education space.
Beyond One-Hot: An Exploration of Categorical Variables
- PyPI - category-encoders - The package page cites the original post
- GitHub - scikit-learn-contrib/category_encoders - README references the post
- Socket.dev - Package security analysis, pulls the PyPI description
- O’Reilly - Python Feature Engineering Cookbook - “See also” section †
- MDPI Symmetry Journal - Academic paper on network anomaly detection, cited in references †
- KDnuggets - Feature Hashing - “In the previous post about categorical encoding…” †
- DZone - Handling Character Data for ML - “You can find more information about these on Will’s blog” †
- Practical Business Python - Guide to encoding categorical values †
- Data Science Diaries - Categorical preliminaries entry †
- Datistics Blog - R to Python migration guide †
- Hypothesis - Annotations tagged “Encoding” †
- University of Ryukyu - Data Mining Course - Japanese university course materials †
- Data Science Stack Exchange - Answer on large dataset encoding †
- Cross Validated - “this article” on mixing continuous and binary data †
BaseN Encoding and Grid Search
- GitHub - scikit-learn-contrib/category_encoders - Also cited in the README
- University of Ryukyu - Data Mining Course - Japanese university course materials †
- Libraries.io - category-encoders - Package page †
Hashing Encoder (previously “Even Further Beyond One-Hot: Hashing”)
- O’Reilly - Python Feature Engineering Cookbook - “See also” section †
- Data Science Stack Exchange - “You can use the feature hashing trick” †
Elote / Rating Systems
- The Cricademic Group - “Using Elo Ranking to Create a College Cricket Top 25” - Links to the elote docs’ Elo page while building a college cricket ranking
Decision Making & Strategy
- Peter Matthews - “Thinking as a General Purpose Technology” - Actual engagement with the ideas, not just a link
- Grokipedia
The Speed-Quality Paradox: When Fast Decisions Kill Startups
- Rodobo - Spanish newsletter on “positive friction”
Data-Driven Decisions vs. Data-Justified Decisions
- Calypso - “Red Flags That Your Decision Process Is Being Driven by Convenient Data, Not Useful Data”
- Calypso - “Your Team Is Not Data-Driven, It Is Confirmation-Driven: How to Fix the Workflow”
AI & Development Tools
AI Prompts for Real Life: Templates That Actually Work
- Trade Talk Podcast (iHeart) - Linked in show notes for an episode on AI tools in construction
- Contractors Connect - Podcast recap post
I Tested LLM Prompt Caching With Anthropic and OpenAI
AI Regulation One Year Later: What Changed in 2025
Data Science & Engineering
Tendencies of Data Engineers and Scientists
- Open Data Science - Republished with “Original Source” attribution
- Data Engineering Podcast - RSS feed links to the post †
Common Data Pitfalls for Recurring ML Systems
- DataMiningApps - Web Picks - “A very relevant post describing the issues one may encounter” †
Python Libraries
Estimating Time Spent on a Project with git-pandas
- Stack Overflow - “a blog post about getting time estimates using git pandas” †
- Hacker News - “Analyze git repositories with pandas” †
- neurocline.github.io - Recent links roundup †
GitHub Cumulative Blame in 5 Lines
- Python Digest (Russian) - “Visualization of GitHub profile activity” †
Create a pip-installable Python Package in 2 Minutes
- Awesome Open Source - Cookiecutter Pipproject - “here” †
- Simply Python - “Will McGinnis’ post” †
- J. Triveri - “Geohashing for Fun and Profit” - Implements geohash encoding from scratch and validates the output against
pygeohash - The EASIER Data Initiative - “Proof of concept for querying spatial data on IPFS using geohash” - Links directly to the GitHub repo while demonstrating geohash-based spatial queries on IPFS
- Medium - “Processing Large Geospatial Dataset Using Geohash Spatial Index”
- Python-bloggers - “GeoHashing from Scratch in Python” - Syndicated republish of the jtrive.com post, same pygeohash validation
Startups & Business
Great Pitch Decks (old page, no longer available)
- Yet Another Data Blog - “pitch decks” †
General Site References
- llmstxt.site - Listed in the llms.txt directory
- Crunchbase - Profile links here
- Atlanta AI Dinner - References the restaurant guide for dinner location ideas
- GitHub - rushter/data-science-blogs - Listed as “Will’s Noise” in curated data science blogs †
- Medium - Random Nerd - “Curated List of 100+ Data Science Resources” †
- Data Science Central - Profile page †
- Get Free Ebooks - Listed under data science resources †
- Data Engineering Podcast - Episode 19 - Guest episode on data teams †
† Links to the old domain (willmcginnis.com). Redirects are in place but the referring pages haven’t updated their links.
Last updated: August 2026