Semi-Supervised Learning

Unlocking Data Potential by Combining Labelled and Unlabelled Insights

Most of your data sits unlabeled, and that's not a problem to solve, it's an opportunity to leverage. Semi-supervised learning sits between the fully labeled and the entirely unlabeled, using a small amount of guidance to make sense of the larger, messier whole. This primer walks through the algorithms that make that possible and, just as importantly, where they stumble. It's a practical read for anyone who wants to get more from their data without drowning in annotation costs.