Machine learning and statistics with python

 Introduction:   In text mining algorithms, as well as nlp based data modeling, word similarity is a very common feature. Word similarity in nlp context refers to semantic similarity between two words, phrases or even two documents. We will discuss how to calculate word similarity using spacy library. what is similarity in NLP and how is it calculated? In NLP, lexical similarity refers between two texts refer to the degree by which the texts has same literal and semantic meaning. i.e. how much similar the texts mean; is calculated by similarity metrics in NLP. There are many different ways to create word similarity features; but the core logic is mostly same in all cases. The core logic in all these cases is to create two representative vectors of the two items; using either universal vectors created from pre-trained models like word2vec, glove, fasttext, bart and others; or using the present document and using different methods like tf-idf match, pagerank procedures, etc....