Tutorial: Natural Language Processing

Instructor: Grishma Jena

How can computers interpret something so human like language? Can they actually understand what we are saying or are they hiding behind a façade of rules and algorithms? How do these systems of zeroes and ones make sense of words? This workshop introduces Natural Language Processing in Python and sheds light on how computers interpret our language. Attendees are introduced to NLTK and Gensim that help them tokenise, process and represent textual data. We will see how data is distilled into different linguistic features that power Machine Learning applications like text classifier, sentiment analyser and topic modeler.

We will be using Jupyter to execute Python code for the purpose of this Natural Language Processing tutorial. It is highly recommended to use Python 3 as Python 2 will be has been sunset on January 1, 2020. A virtual environment can be used to manage and isolate the packages for our project. Please follow these instructions to have all the dependencies ready before the tutorial as that will enable us to hit the ground running.

Pre-requisites

Using Jupyter on your local machine

Requires installation of packages but you will be able to use Jupyter and run code offline.

1. Ensure that pip is installed and upgrade it. Pip should already be available if you are using Python 2 >= 2.7.9 or Python 3 >= 3.4 downloaded from python.org. For further installation instructions check this.

2. Optional: If you plan on using a virtual environment, ensure virtualenv (Python 2) or venv (Python 3) is installed. Create a virtual environment and activate it. Detailed instructions here.

3. Install the required packages using pip in the terminal:

• Python 3:

python3 -m pip install jupyter nltk lxml requests matplotlib scikit-learn
wikipedia gensim wordcloud --user

If you face problems installing NLTK, take a look at this or try with Python 3.

4. Open a Jupyter notebook with jupyter notebook in your terminal. This opens in your browser at default port 8888.

5. Download the sample notebook ‘Introduction to NLP test’ and open it in Jupyter. Execute the code by clicking on Cell -> Run Cells. Check out this video for a quick introduction to Jupyter.

Feel free to contact me in case of any queries.