Goal
Implement topic modeling on Texthero.

Topic modeling
There are mainly two ways to do topic modeling: LSA/LSI (latent semantic indexing) and LDA (Latent Dirichlet allocation). This simple tutorial explains how to implement it in python.

Python implementation
LSA/LSI is just basically TF-IDF + SVD. What's it's important is to understand how to visualize and how to return the topic model information from the function.

Documentation
Other than adding the docstring, it's probably useful to write a "getting started" tutorial on how topic modeling works and how to use Texthero's function.

We will probably want to implement both LSI and LDA, in two? separate functions.

This issue is a work in progress. Any help is very appreciated!