Data Science, Machine Learning, NLP, Transformers, Word Embeddings.
tfidf_vectorizer = TfidfVectorizer() tfidf = tfidf_vectorizer.fit_transform(corpus).toarray() sns.heatmap(tfidf, annot=True, cbar = False, xticklabels = vocab) Image is created by Rostyslav Neskorozhenyi with seaborn module Word2Vec and GloVe The most commonly used models for word embeddings are