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GLOSSARY · W

What Is Word Embedding?

DEFINITION

Word embedding is a natural language processing (NLP) technique that converts words and text into numbers. This lets a machine learning algorithm understand the context of words. Word vectors show the relationships between words based on their meaning.

Why use it?

  • Text can be converted into numerical form.
  • AI models can understand the relationships between words.
  • Text can be categorized more effectively.
  • Information can be retrieved based on similarity.

When to use it?

  • Building a semantic search engine.
  • Chatbots and virtual assistants.
  • Product recommendations.
  • Sentiment analysis.
  • Categorizing documents and clustering text.

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