semi-supervised-learning

Vocabulary Word

Definition

'Semi-supervised learning' is a type of artificial intelligence learning where the computer learns from both labelled data and unlabelled data. Think of it like learning a language by vocabulary words and then some random conversations without translations.

Examples in Different Contexts

In natural language processing (NLP), semi-supervised learning helps improve language models by leveraging both labeled and unlabeled text data. An NLP engineer might say, 'We use semi-supervised learning to enhance our language models' understanding of context and semantics.'

Practice Scenarios

Innovation

Scenario:

We've been lagging in updating our prediction models. It's essential we find a way to make our AI adapt faster to the evolving data patterns.

Response:

You're absolutely right. We should explore adopting semi-supervised learning to hasten our AI system's adaptability.

Scenario:

Our text recognition system needs an upgrade. It's not performing up to the mark with only handwritten texts.

Response:

I agree. Implementing a semi-supervised learning approach might significantly improve our text recognition capabilities.