ML & Data Science
- ExplainerAI Foundations · Explained
What Are Embeddings? How Meaning Becomes Math
An embedding turns meaning into a location so that similarity becomes distance. That one idea is the engine under semantic search, recommendations, and the retrieval half of every RAG system, and it is cheap enough to run on your own data.
Ibrahim Denis Fofanah·Sep 25, 2026·7 min
- Deep DiveData Storytelling · Craft
Data Storytelling Teaches You to Present a Finding. Nobody Teaches You to Find One.
Every guide teaches you to present a finding. Almost none teach you to find one. The four questions that break a story open, and a real Sierra Leone trial where every write-up missed it.
Ibrahim Denis Fofanah·Sep 25, 2026·7 min
AnalysisData Engineering · PerformanceOpenAI Got 6× Better CPU Efficiency With Rust. The Lesson Is Why They Waited.
OpenAI’s storage service once pushed more than 20 million requests per second through Python. A Rust rewrite later delivered 6× better CPU efficiency and 15× better memory efficiency. The useful engineering lesson is not “rewrite everything in Rust.” It is why OpenAI knowingly carried the slower system first.
Ibrahim Denis Fofanah·Sep 25, 2026·16 min
- ExplainerFrom Notebook to Production · Part 1
Your Model Works in a Notebook. That Is the Easy Part.
A notebook proves a model can work once. Production requires it to work continuously, on unseen data, within a budget, and to fail safely. The five questions that define the gap, and why deployment is the scarce skill.
Ibrahim Denis Fofanah·Sep 25, 2026·7 min
TutorialSQL · Data QualityYour SQL Query Did Not Fail. NULL Changed the Question.
NULL does not mean zero, blank, or false. It introduces UNKNOWN, and that third truth value can quietly change filters, exclusions, joins, and aggregates.
Ibrahim Denis Fofanah·Sep 25, 2026·10 min
TutorialAnalytics Engineering · Metrics · Semantic LayerYour KPI Needs a Contract: Build Metrics That Survive Dashboards and AI
A metric is more than an aggregation. Define its entity, grain, time, eligibility, joins, tests, and change policy so dashboards and AI return the same answer.
Ibrahim Denis Fofanah·Sep 25, 2026·9 min
TutorialData Engineering · ReliabilityYour Pipeline Passed. Your Dashboard Is Still Wrong.
A green pipeline only proves the code ran. This practical guide shows how contracts, freshness checks, semantic tests, lineage, and safe promotion catch schema drift before it corrupts a dashboard.
Ibrahim Denis Fofanah·Sep 11, 2026·7 min
- TutorialModel Evaluation · Time Series
Your Train-Test Split Is Leaking the Future
A random split can make a forecasting model look excellent by training on records that occur after its test rows. Here is how to build a time-aware evaluation that rehearses production instead of leaking the future.
Ibrahim Denis Fofanah·Sep 7, 2026·10 min
- ExplainerML & Data Science · Under the Hood
Reasoning Models Explained: What Test-Time Compute Actually Costs You
Letting a model think longer is a real capability (DeepSeek-R1 lifted AIME accuracy from 15.6% to 71.0%) and a real bill you pay in tokens and latency on every query. When it is worth paying, and when it is not.
Ibrahim Denis Fofanah·Aug 11, 2026·7 min
- ExplainerFrom Notebook to Production · Part 2
Serving a Model: Endpoint, Batch, or Embedded?
Three ways to serve a model, endpoint, batch, or embedded, and the one question that decides which. Most people default to the always-on endpoint. It is the priciest and most fragile option, and usually the wrong one.
Ibrahim Denis Fofanah·Aug 8, 2026·7 min
- TutorialData Thinking · Part 3
Before You Clean Your Data, Ask This One Question: Is It Actually Dirty?
A lender's income field was 23% empty, and the gap turned out to be the best feature in the dataset. Three mechanisms behind missing data, four diagnostics that tell them apart, and why cleaning is a provenance problem in disguise.
Ibrahim Denis Fofanah·Jul 28, 2026·12 min
ExplainerData Thinking · Part 1The First Question Every Data Scientist Asks: What Does One Row Represent?
A falling average order value triggered a discount review. The arithmetic was right and the table was wrong. Why the grain of a table decides whether every metric built on top of it is true.
Ibrahim Denis Fofanah·Jul 23, 2026·12 min