How to Train Bag of Words Model?

I had previously mentioned, that you need context words and center words to train your continuous bag-of-words model. The question now is, how do you actually get these words? Let&dive in. Previously, you cleaned and tokenized the corpus, and you now have this clean corpus as an array of words or tokens. Now, I will show you how to extract center words and their context words, which will serve as examples to train the continuous bag-of-words model. Here&the code to do this in Python. The get_windows function takes two arguments, words, which is an array of words, or tokens. But I&stick with the term words here. The context have size stored in the variable C, which is the number of words to be taken on each side of the center word. This was 2 in the previous video, for a total window size of 5. The function initializes a counter with the index of the first word that has enough words before it. In the working example, I am happy because I am learning, the tokenized array would be, I am...