Natural Language Processing

In this article, we will discuss bag of words (BOW) model building in natural language processing. Sometimes, we try to find the occurrence of the words in the text document and we try with a simple count method to search the count of the one word. But if we want to know the occurrence of each word in the text document and with its count then we use the bag of words method also known as word embeddings. The bag of words is used to extract the information from the text and trying to make them a dictionary or histogram with its word counts. Let's have an example with this sentence below: In these sentences, we first break them into tokens and remove all punctuation and symbols from the sentences to make a model to further analysis with algorithms.