Machine learning, explained with real numbers
Short lessons in plain language — no math background needed. Every idea is taught through a worked example you can follow by hand, and every term links to a bilingual glossary aligned with the official SDAIA AI glossary.
The lessons
Six short reads, in order — or jump straight to the one you need.
What is a model & how training works
Where the "model" actually comes from: training, testing, and why holding data back matters.
Read the lessonRegression by worked example
Predict a number — five houses, one formula, and every error metric worked out by hand.
Read the lessonClassification by worked example
Predict a category — ten customers, a hand-filled confusion matrix, and what accuracy hides.
Read the lessonForecasting: sales next month
Predict the future from the past — lags, horizon, and why far-out forecasts drift.
Read the lessonUnderstanding your metrics
R², MAE, precision, recall and friends — what each score means and when to trust it.
Read the lessonReading your dataset report
The thirty-ish automatic checks Bayanii runs on your data, and what each finding asks of you.
Read the lessonEvery term, in both languages
The glossary defines every metric and concept the lessons use — in plain English and Arabic, with a tiny worked example for each. Arabic terms follow the official SDAIA AI glossary.