Book Image

Mastering spaCy

By : Duygu Altınok
Book Image

Mastering spaCy

By: Duygu Altınok

Overview of this book

spaCy is an industrial-grade, efficient NLP Python library. It offers various pre-trained models and ready-to-use features. Mastering spaCy provides you with end-to-end coverage of spaCy's features and real-world applications. You'll begin by installing spaCy and downloading models, before progressing to spaCy's features and prototyping real-world NLP apps. Next, you'll get familiar with visualizing with spaCy's popular visualizer displaCy. The book also equips you with practical illustrations for pattern matching and helps you advance into the world of semantics with word vectors. Statistical information extraction methods are also explained in detail. Later, you'll cover an interactive business case study that shows you how to combine all spaCy features for creating a real-world NLP pipeline. You'll implement ML models such as sentiment analysis, intent recognition, and context resolution. The book further focuses on classification with popular frameworks such as TensorFlow's Keras API together with spaCy. You'll cover popular topics, including intent classification and sentiment analysis, and use them on popular datasets and interpret the classification results. By the end of this book, you'll be able to confidently use spaCy, including its linguistic features, word vectors, and classifiers, to create your own NLP apps.
Table of Contents (15 chapters)
1
Section 1: Getting Started with spaCy
4
Section 2: spaCy Features
9
Section 3: Machine Learning with spaCy

Understanding the basics of text classification

Text classification is the task of assigning a set of predefined labels to text. Given a set of predefined classes and some text, you want to understand which predefined class this text falls into. We have to determine the classes ourselves by the nature of our data before starting the classification task. For example, a customer review can be positive, negative, or neutral.

Text classifiers are used for detecting spam emails in your mailbox, determining the sentiment of customer's reviews, understanding customer's intent, sorting customer's complaint tickets, and so on.

Text classification is a fundamental task of NLP. It is gaining importance in the business world, as it enables businesses to automate their processes. One immediate example is spam filters. Every day, users receive many spam emails but most of the time never see these emails and don't get any notifications because spam filters save the users...