This is code I wrote for courses I teach at Indiana University. The first parts of the code in this tutorial are meant for Python beginners, and the code grows more advanced as you advance through the later parts.

In the context of this tutorial, I plan to include sections covering the Natural Language Toolkit (NLTK), gensim, scikit-learn, visualization, numpy, etc.

In addition, I plan to add more advanced code covering practical machine learning issues like vector space models to perform certain tasks like sentiment analysis.

Finally, I also plan to introduce some deep learning tools and provide some relevant code.

The courses teach skills for at the intersection of fields like natural language processing, machine learning, social media mining, text mining, data science, etc.

The code is written primarily in Python 2.7. A migration to Python 3 shoul be straightforward. Some of the code is written and run during class sessions and so it is shared without much polishing. I provide some comments, before I push here, as much as I can.