CSharp-Coder

Learn how to build an AI recommendation system in C# using ML.NET collaborative filtering and matrix factorization. Full code, best practices — start today. Every product team eventually gets the same request: "Can we show users what they'll probably like next?" If your stack is .NET, you don't need Python, a separate microservice, or a data science team to answer that. You can build a production-grade recommendation system in C# using ML.NET's matrix factorization trainer — the same collaborative filtering technique that powers the "because you watched…" rails on major streaming platforms. This tutorial walks through the full pipeline: loading rating data, training a model, evaluating it honestly, generating top-N recommendations, and shipping it inside an ASP.NET Core API. What Collaborative Filtering Actually Does Collaborative filtering makes a deceptively simple bet: people who agreed in the past will agree in the future . It ignores what a...