Now that we know what vector transformations are, let's get used to creating them, and using them. We will be performing these transformations with Gensim, but even scikit-learn can be used. We'll also have a look at scikit-learn's approach later on.
Let's create our corpus now. We discussed earlier that a corpus is a collection of documents. In our examples, each document would just be one sentence, but this is obviously not the case in most real-world examples we will be dealing with. We should also note that once we are done with preprocessing, we get rid of all punctuation marks - as for as our vector representation is concerned, each document is just one sentence.
Of course, before we start, be sure to install Gensim. Like spaCy, pip or conda is the best way to do this based on your working environment.
from gensim import corpora documents = [u"Football club Arsenal defeat local rivals this weekend.", u"Weekend football frenzy takes over London.", u"Bank...
