Semantic Networks
Machine Learning
A learning approach where the training data provides its own supervision by leveraging the underlying structure in the data.
Detailed Explanation
Self-supervised learning is a machine learning approach where models learn to understand data patterns using automatically generated labels derived from the data itself. This method eliminates the need for manual labeling by exploiting inherent structures, such as predicting missing parts or reconstructing input data, enabling effective representation learning that can be transferred to various downstream tasks.
Use Cases
- •Automatically label large datasets for image recognition, reducing manual effort and improving model generalization.
Related Terms
Other terms in the Machine Learning category