In this chapter, we will look at an amazing and simple concept called word to vector (word2vec). This concept was developed by a team of researchers led by Tomas Mikolov at Google. As we all know, Google provides us with a lot of great products and concepts. Word2vec is one of them. In NLP, developing tools or techniques that can deal with the semantics of words, phrases, sentences, and so on are quite a big deal, and the word2vec model does a great job of figuring out the semantics of words, phrases, sentences, paragraphs, and documents. We are going to jump into this vectorization world and live our life in it for a while. Don't you think this is quite amazing? We will be starting from the concepts and we will end with some fun and practical examples. So, let's begin.
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