An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec

Introduction Before we start, have a look at the below examples. You open Google and search for a news article on the ongoing Champions trophy and get hundreds of search results in return about it. Nate silver analysed millions of tweets and correctly predicted the results of 49 out of 50 states in 2008 U.S … Continue reading An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec