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 natural language processing (NLP), transfer learning is used to apply knowledge from one language task to another, enhancing model performance on tasks like translation or sentiment analysis. An NLP engineer might state, 'We utilized transfer learning from a large language dataset to improve our chatbot's understanding of user queries.'

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.