Building a Rock Music Recommender with ML.NET: From Training to Model Evaluation

I've just published a practical series about building a music recommendation system using ML.NET and ASP.NET Core.

The goal wasn't just to train a recommendation model, but to explain the complete workflow, from understanding how recommendation systems work to evaluating whether the model is actually good enough to be used in a real application.

The series covers:

🎸 How recommendation systems work

📊 How to evaluate a recommendation model

🤖 Training a rock music recommender with ML.NET

📈 Evaluating the recommender's performance

🚀 Exposing the model through an ASP.NET Core Web API

Articles:

[https://devfullstack.net/blog/how-recommendation-systems-work](https://devfullstack.net/blog/how-recommendation-systems-work)

[https://devfullstack.net/blog/how-to-evaluate-a-recommendation-model](https://devfullstack.net/blog/how-to-evaluate-a-recommendation-model)

[https://devfullstack.net/blog/training-a-rock-recommender-with-mlnet](https://devfullstack.net/blog/training-a-rock-recommender-with-mlnet)

[https://devfullstack.net/blog/evaluating-the-rock-recommender](https://devfullstack.net/blog/evaluating-the-rock-recommender)

[https://devfullstack.net/blog/building-the-rock-recommender-api](https://devfullstack.net/blog/building-the-rock-recommender-api)