Book Image

Python Natural Language Processing Cookbook

By : Zhenya Antić
Book Image

Python Natural Language Processing Cookbook

By: Zhenya Antić

Overview of this book

Python is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization. Starting with an overview of NLP, the book presents recipes for dividing text into sentences, stemming and lemmatization, removing stopwords, and parts of speech tagging to help you to prepare your data. You’ll then learn ways of extracting and representing grammatical information, such as dependency parsing and anaphora resolution, discover different ways of representing the semantics using bag-of-words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques. As you advance, you’ll also see how to extract information from text, implement unsupervised and supervised techniques for topic modeling, and perform topic modeling of short texts, such as tweets. Additionally, the book shows you how to develop chatbots using NLTK and Rasa and visualize text data. By the end of this NLP book, you’ll have developed the skills to use a powerful set of tools for text processing.
Table of Contents (10 chapters)

Using BERT instead of word embeddings

A recent development in the embeddings world is BERT, also known as Bidirectional Encoder Representations from Transformers, which, like word embeddings, gives a vector representation, but it takes context into account and can represent a whole sentence. We can use the Hugging Face sentence_transformers package to represent sentences as vectors.

Getting ready

For this recipe, we need to install PyTorch with Torchvision, and then the transformers and sentence transformers from Hugging Face. Follow these installation steps in an Anaconda prompt. For Windows, use the following code:

conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
pip install transformers
pip install -U sentence-transformers

For macOS, use the following code:

conda install pytorch torchvision torchaudio -c pytorch
pip install transformers
pip install -U sentence-transformers

How to do it…

The Hugging Face code makes using BERT very easy. The...