Data Cleaning — Complete Guide
Data Cleaning — 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 25 of 100
Data Cleaning
Foundations ✓ → Models → NLP & advanced → MLOps
Models · 2 — Classify & regress · ~6 min · Module 3: ML.NET Pipelines
What is this?
Cleaning removes bad rows, fixes types, and drops duplicates before training.
Why should you care?
AIPredict garbage amounts and duplicate txs poison fraud models.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
rows = rows.Where(r => r.Amount > 0 && r.Amount < 1_000_000)
.GroupBy(r => r.TxId).Select(g => g.First()).ToList();
var data = ml.Data.LoadFromEnumerable(rows);What happened?
- Clean in C#/SQL before IDataView when possible.
- Log how many rows you dropped.
Practice next
- Filter impossible Amount.
- Dedupe TxId.
- Log drop counts.
- Cap outliers at p99.
- Reject null MerchantCategory.
Remember
Filter + dedupe. Log drops. Then load.
AIPredict clean train set
Duplicates and junk amounts removed.
Outcome: Stable training curves.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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