Semi-Supervised Learning: Navigating Challenges and Charting Future Directions
Jame zazzdy, fidelicy flex · 2023
Semi-supervised learning is a subfield of machine learning that bridges the gap between supervised learning, where models are trained on labeled data, and unsupervised learning, where models learn from unlabeled data. In recent years, semi-supervised learning has gained significant attention for its potential to make the most of limited labeled data while harnessing the information within massive unlabeled datasets. This article explores the concept of semi-supervised learning, highlights the challenges it faces, and discusses the exciting future directions of this field