Semi-Supervised Learning: The Best of Both Worlds
Combining small amounts of labeled data with large amounts of unlabeled data to improve model accuracy and reduce labeling costs.
Combining small amounts of labeled data with large amounts of unlabeled data to improve model accuracy and reduce labeling costs.