Book Image

Natural Language Processing and Computational Linguistics

By : Bhargav Srinivasa-Desikan
Book Image

Natural Language Processing and Computational Linguistics

By: Bhargav Srinivasa-Desikan

Overview of this book

Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Installation


Let's get started with setting up and installing spaCy. spaCy is compatible with 64-bit CPython [8] 2.6+∕3.3+ and runs on Unix/Linux, macOS/OS X, and Windows. CPython is a reference implementation of Python written in C – we don't need to know the details behind it, and if you have a stable installation of Python running, it is likely your CPython modules are just fine as well. The latest spaCy releases are available over Pip [9] (source packages only) and Conda [10]. Pip and conda are two Python package distributors. Installation requires a working build environment. We will be using Python 3, though the examples are all valid for Python 2 as well.

Pip remains the most straightforward choice, but for users with anaconda installed, they will be using conda instead.

pip install -U spacy

Note

When using pip, it is generally recommended that you install packages in a virtualenv tool to avoid modifying system state.

Since we will be downloading a number of Python packages throughout...