Building an On-Device Training Strategy for Personalized iOS Apps

Machine learning on mobile devices is often associated with inference: download a model, run predictions, and return results.

But what if the model could continue learning directly on the user's device?

In this article, I'll walk through a practical training strategy for on-device personalization in iOS using a lightweight Multilayer Perceptron (MLP). The goal is to create applications that adapt to individual users while keeping their data private and avoiding cloud infrastructure.

Why Train On Device?

Consider a habit-tracking application.