Visualizing an LDA model, using Python

I have a LDA model with the 10 most common topics in 10K documents. Now it's just an overview of the words with corresponding probability distribution for each topic.

I was wondering if there is something available for python to visualize these topics?

How do you visualize LDA?

A latent Dirichlet allocation (LDA) model is a topic model which discovers underlying topics in a collection of documents and infers word probabilities in topics. You can visualize the LDA topics using word clouds by displaying words with their corresponding topic word probabilities.

PyLDAVis - Visualization tool for LDA Models

Useful article for learning Topic Modelling using different models in Python