What are neural networks and how do they work in NLP?

What are neural networks and how do they work in NLP?

Neural networks are computational models inspired by the human brain, used in NLP to understand and generate human language.

Can you explain how they differ from traditional algorithms?

Unlike traditional algorithms that rely on predefined rules, neural networks learn patterns from data, making them more adaptable.

What are some common applications of neural networks in NLP?

Common applications include sentiment analysis, machine translation, and chatbots, which all benefit from understanding context.

How do neural networks handle ambiguity in language?

They use context and training data to disambiguate meanings, often employing techniques like attention mechanisms.

What are the challenges faced when using neural networks for NLP?

Challenges include data quality, computational resources, and the need for large datasets to train effectively.