Demystifying Word2Vec: Understanding Word Embeddings for Natural Language Processing
Word embeddings are a popular technique in natural language processing (NLP) that represents words or phrases as dense vectors in a continuous vector space. They capture the semantic and syntactic relationships between words, allowing machines to understand and process human language more effectively.
Traditionally, NLP models represented words as one-hot