Demand Prediction — Complete Guide
Demand Prediction — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ML.NET Tutorial on Toolliyo Academy.
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ML.NET Tutorial · Lesson 45 of 100
Demand Prediction
Foundations ✓ → Models → NLP & advanced → MLOps
Models · 2 — Classify & regress · ~6 min · Module 5: Regression Models
What is this?
Demand prediction estimates how much customers will want — feeds inventory and staffing.
Why should you care?
AIPredict warehouses order against demand models, not last week alone.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
var pipe = ml.Forecasting.ForecastBySsa("Forecast", "Demand", windowSize: 14, seriesLength: 60, trainSize: 120, horizon: 14);
var model = pipe.Fit(history);
var forecast = (model as ITransformer) /* use forecasting engine pattern */;What happened?
- SSA for univariate series; regression with promos for richer features.
- Keep horizon clear to ops.
Practice next
- SSA 14-day horizon.
- Compare to regression+promo.
- Share horizon in API docs.
- Horizon 7 vs 14 MAE.
- Add stockout days as zero-demand carefully.
Remember
Clear horizon. SSA or feature regression. Ops-aligned output.
AIPredict demand API
Warehouse pulls 14-day Forecast.
Outcome: Purchase orders match horizon.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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