Neural Network Embeddings in AI
What are neural network embeddings?
Embeddings are a way to convert features, like words or items, into vectors of real numbers. The idea is that the embedding vectors of relevant features will have a small distance in the embedding space. That is, related words in the embedding space have similar vectors. This is crucial in tasks like natural language processing for chatbots, recommendation systems, and more, making AI models more nuanced and effective. For example, "Apple," even though a fruit, may have an embedding vector similar to the embedding vector of the word "technology." The words king and queen are related and hence might have similar vectors.
Dr. Shahriar Hossain
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