Machine Learning, NLP, Word Embeddings, Artificial Intelligence, Text Similarity.
example “New York” will be considered as a single word in bi-gram. The vector generated using TF-IDF is sparse. It gives zero TF-IDF score for the words which are not present in the document. Word2vec Using Word2Vec embeddings, word will be represented as a multidimensional array. The two