This is the code repository for Python Natural Language Processing, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
This book starts off by laying the foundation for Natural Language Processing and gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
import nltk
from nltk.corpus import brown as cb
from nltk.corpus import gutenberg as cg
Let's discuss some prerequisites for this book. Don't worry, it's not math or statistics, just basic Python coding syntax is all you need to know. Apart from that, you need Python 2.7.X or Python 3.5.X installed on your computer; I recommend using any Linux operating system as well. The list of Python dependencies can be found at GitHub repository at https://github.com/jalajthanaki/NLPython/blob/master/pip-requirements.txt. Now let's look at the hardware required for this book. A computer with 4 GB RAM and at least a two-core CPU is good enough to execute the code, but for machine learning and deep learning examples, you may have more RAM, perhaps 8 GB or 16 GB, and computational power that uses GPU(s).