So far, we haven't spoken much about finding hidden information - more about how to get our textual data in shape. We will be taking a brief departure from spaCy to discuss vector spaces and the open source Python package Gensim - this is because some of these concepts will be useful in the upcoming chapters and we would like to lay the foundation before moving on. However, we'll only be touching the surface of Gensim's capabilities. This chapter will introduce you to the data structures largely used in text analysis involving machine learning techniques - vectors [1].
This means that we are still in the domain of preprocessing and getting our data ready for further machine learning analysis. It may seem like overkill, focusing so much on just setting up our text/data, but like we've said before - garbage in, garbage out. While the previous...
