NLP, Llm, Deep Learning, Machine Learning, Mathematics.
workers=4) # Access embeddings word_embeddings = model.wv print(word_embeddings['natural']) In summary, Word2Vec’s mechanics involve training neural network models (CBOW and Skip-gram) to learn vector representations that effectively capture semantic relationships between words. The resulting