Book Image

Mastering spaCy

By : Duygu Altınok
5 (1)
Book Image

Mastering spaCy

5 (1)
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

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Finally, the validation_split parameter is used to evaluate the experiment."

A block of code is set as follows:

import spacy
nlp = spacy.load("en_subwords_wiki_lg")

Any command-line input or output is written as follows:

wget  https://github.com/PacktPublishing/Mastering-spaCy/blob/main/Chapter08/data/Reviews.zip

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "The following diagram illustrates the distance between dog and cat and the distance between dog, canine terrier, and cat:"

Tips or important notes

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