NLP Basics — Complete Guide
NLP Basics — 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 15 of 100
NLP Basics
Foundations → Models → NLP & advanced → MLOps
Foundations · 1 — Context & data · ~6 min · Module 2: Machine Learning Basics
What is this?
NLP turns text into features — tokens, n-grams, embeddings — for sentiment and classification.
Why should you care?
AIPredict reviews and support tickets are text-heavy inputs.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
var textPipeline = ml.Transforms.Text.FeaturizeText("Features", "ReviewText")
.Append(ml.BinaryClassification.Trainers.SdcaLogisticRegression());What happened?
- FeaturizeText is a strong baseline.
- Clean HTML/emoji before training.
- Keep language consistent per model.
Practice next
- FeaturizeText on ReviewText.
- Train sentiment binary.
- Predict one review.
- Add StopWordsRemoving estimator.
- Try bigrams via TextFeaturizingEstimator options.
Remember
Text → features. FeaturizeText baseline. Clean input.
AIPredict review NLP
Product reviews train a sentiment model.
Outcome: Dashboard shows % positive.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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