Data science

Practical data science, from messy questions to useful evidence.

Projects and writing that show the reasoning behind analysis — not just the final chart or model.

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Writing

Data Science·June 29, 2026·7 min read

Opening the black box: explaining the model with SHAP

What SHAP actually measures, a real customer's score broken down feature by feature, and three different views of what matters most.

#SHAP#explainable AI#model interpretability#machine learning#Model Evaluation

Data Science·June 26, 2026·6 min read

The Brier score: one number for whether your probabilities can be trusted

A worked example of the Brier score, why it punishes confident wrong answers, and how a badly calibrated model can lose to a trivial guess.

#Brier score#model evaluation#calibration#probability#machine learning#Model Evaluation

Data Science·June 24, 2026·6 min read

Calibration: turning a ranking into a probability you can actually trust

Why class-weighted scores lie about probability, and how Platt scaling and isotonic regression fix it.

#calibration#Platt scaling#isotonic regression#probability#machine learning#Model Evaluation

Data Science·April 11, 2026·6 min read

Context Windows Demystified: How Much Can Your AI Actually Remember?

The finale of our LLM tokenization series: what context windows are, how they relate to token limits, and how real AI products manage them.

#Tokenisation#NLP#Text Processing

Data Science·March 27, 2026·6 min read

Token Limits: Why Your AI Chatbot Suddenly Forgets Everything

A deep dive into how token limits affect the performance of large language models and what you can do about it.

#Tokenisation#NLP#Text Processing

Data Science·March 16, 2026·8 min read

Inside the Tokeniser: BPE, WordPiece, SentencePiece & Unigram Explained

An example-driven walkthrough of the four major tokenisation algorithms behind modern LLMs, with a step-by-step explanation.

#Tokenisation#NLP#Text Processing

Data Science·March 5, 2026·8 min read

Tokens 101: The Secret Language Your AI Actually Speaks

A beginner-friendly introduction to what tokens are, how they differ from words and characters, and why they matter when using LLMs like ChatGPT and Claude.

#Tokenisation#NLP#Text Processing

Data Science·February 28, 2026·12 min read

Clustering in Machine Learning: Finding Hidden Groups in Your Data

A simple introduction to clustering. What it is, how it differs from classification, and real retail examples.

#Clustering#Machine Learning#Unsupervised Learning