Knowledge Graphs
Machine Learning
A model compression technique where a smaller model learns to mimic a larger more complex model's behavior. This allows for creating more efficient models while maintaining performance.
Detailed Explanation
Knowledge Distillation is a process in Machine Learning where a smaller, simpler model is trained to replicate the behavior of a larger, more complex model. By transferring knowledge from the teacher to the student model through soft predictions or intermediate representations, it enables the creation of efficient models that retain high performance, reducing computational costs and improving deployment flexibility.
Use Cases
- •Deploying lightweight AI on mobile devices by distilling complex models into smaller, efficient versions for real-time applications.
Related Terms
Other terms in the Machine Learning category