Collaborative Filtering — Complete Guide

Collaborative Filtering — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ML.NET Tutorial on Toolliyo Academy.

8 min read Updated 8/20/2026

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ML.NET Tutorial · Lesson 52 of 100

Collaborative Filtering

Foundations ✓ → Models ✓ → NLP & advanced → MLOps

NLP & advanced · 3 — Recs, text, ONNX · ~6 min · Module 6: Recommendation Systems

What is this?

Collaborative filtering learns taste from similar users or items — “people like you bought X”.

Why should you care?

AIPredict has sparse ratings; MF discovers latent factors without hand-crafted product features.

See it live — copy this example

Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.

var cf = ml.Recommendation().Trainers.MatrixFactorization(new MatrixFactorizationTrainer.Options {
    MatrixColumnIndexColumnName = "UserKey",
    MatrixRowIndexColumnName = "ItemKey",
    LabelColumnName = "ImplicitFeedback",
    NumberOfIterations = 20
});
var model = ml.Transforms.Conversion.MapValueToKey("UserKey", "UserId")
    .Append(ml.Transforms.Conversion.MapValueToKey("ItemKey", "ProductId"))
    .Append(cf).Fit(clicks);