Machine Learning

Semi-Supervised Learning

Learning from a small labelled dataset combined with a larger unlabelled dataset.

Semi-supervised learning combines a limited amount of labelled data with a much larger collection of unlabelled examples. The model uses the labelled data to understand the task and the unlabelled data to learn broader patterns.

This approach is valuable when collecting raw data is easy but manual annotation is expensive or slow. It is used in image recognition, document classification, speech processing and medical applications.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression

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