NLP Text Classification — Complete Guide
NLP Text Classification — 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 65 of 100
NLP Text Classification
Foundations ✓ → Models ✓ → NLP & advanced → MLOps
NLP & advanced · 3 — Recs, text, ONNX · ~10 min · Module 7: NLP with ML.NET
What is this?
Text classification assigns documents to categories — billing, fraud, shipping — from labeled examples.
Why should you care?
AIPredict routes support tickets automatically instead of manual queue sorting.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
public class TicketRow { public string Subject; public string Body; public string Category; }
var pipe = ml.Transforms.Text.FeaturizeText("SubF", nameof(TicketRow.Subject))
.Append(ml.Transforms.Text.FeaturizeText("BodyF", nameof(TicketRow.Body)))
.Append(ml.Transforms.Concatenate("Features", "SubF", "BodyF"))
.Append(ml.MulticlassClassification.Trainers.SdcaMaximumEntropy());
var model = pipe.Fit(tickets);What happened?
- Multi-class needs MapValueToKey on Label (trainer adds it).
- Concatenate subject + body features for better accuracy.
Practice next
- Featurize subject and body.
- Concatenate Features.
- SdcaMaximumEntropy train.
- Add MapValueToKey on Category explicitly.
- Evaluate macro-F1.
Remember
Multi-class text. Concat fields. Sdca multi trainer.
AIPredict ticket router
New ticket auto-tagged Billing vs Fraud.
Outcome: Queue assignment without manual triage.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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