transfer-learning

Vocabulary Word

Definition

Transfer learning is a type of machine learning. If a machine learns how to do one task really well, transfer learning means using what it learned from that task to help it learn a new but similar task.

Examples in Different Contexts

In computer vision, transfer learning enables the application of models trained on large datasets to similar but smaller problems. A computer vision engineer might explain, 'Transfer learning is essential for our project because it allows us to apply state-of-the-art models to our specific image recognition challenges.'

Practice Scenarios

Tech

Scenario:

Developing a model from scratch will take a lot of computational resources. We can brainstorm some ideas for how to improve.

Response:

Wouldn't transfer learning be a great fit here? We could use existing models as starting points.

Scenario:

The currently available language models aren't specific enough for our needs. We should explore different methods to address this.

Response:

Perhaps we could consider applying transfer learning? We could have the system learn from an existing, more general language model.