Training Pipelines — Complete Guide
Training Pipelines — 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 23 of 100
Training Pipelines
Foundations ✓ → Models → NLP & advanced → MLOps
Models · 2 — Classify & regress · ~6 min · Module 3: ML.NET Pipelines
What is this?
Training pipelines Append a trainer after features and Fit on the train set.
Why should you care?
AIPredict experiments swap trainers while keeping features stable.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
var trainPipe = Features()
.Append(ml.BinaryClassification.Trainers.FastTree());
var model = trainPipe.Fit(trainSet);What happened?
- Keep hyperparameters in options objects.
- Log trainer name with metrics.
Practice next
- FastTree train.
- Sdca train.
- Compare AUC.
- Change NumberOfTrees.
- Save winner zip only.
Remember
Features + trainer. Log options. Hold out test.
AIPredict trainer bake-off
FastTree vs Sdca on same features.
Outcome: Winner promotes with metrics.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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