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Mastering spaCy

You're reading from Mastering spaCy An end-to-end practical guide to implementing NLP applications using the Python ecosystem

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781800563353

Length 356 pages

Edition 1st Edition

Languages

Python

Tools

Spacy

Concepts

Mobile Application Development

Author (1):

Duygu Altınok

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Getting Started with spaCy

2. Chapter 1: Getting Started with spaCy FREE CHAPTER

3. Chapter 2: Core Operations with spaCy

4. Section 2: spaCy Features

5. Chapter 3: Linguistic Features

6. Chapter 4: Rule-Based Matching

7. Chapter 5: Working with Word Vectors and Semantic Similarity

8. Chapter 6: Putting Everything Together: Semantic Parsing with spaCy

9. Section 3: Machine Learning with spaCy

10. Chapter 7: Customizing spaCy Models

11. Chapter 8: Text Classification with spaCy

12. Chapter 9: spaCy and Transformers

13. Chapter 10: Putting Everything Together: Designing Your Chatbot with spaCy

14. Other Books You May Enjoy

Sentiment analysis with spaCy

In this section, we'll work on a real-world dataset and train spaCy's TextCategorizer on this dataset. We'll be working on the Amazon Fine Food Reviews dataset (https://www.kaggle.com/snap/amazon-fine-food-reviews) from Kaggle in this chapter. The original dataset is huge, with 100,000 rows. We sampled 4,000 rows. This dataset contains customer reviews about fine food sold on Amazon. Reviews include user and product information, user rating, and text.

You can download the dataset from the book's GitHub repository. Type the following command into your terminal:

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

Alternatively, you can click on the URL in the preceding command and the download will start. You can unzip the zip file with the following:

unzip Reviews.zip

Alternatively, you can right-click on the ZIP file and choose Extract here to inflate the ZIP file....

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Authors (1)

Duygu Altınok

Duygu Altınok

Duygu Altınok is a senior NLP engineer with 12 years of experience in almost all areas of NLP including search engine technology, speech recognition, text analytics, and conversational AI. She authored several publications in the NLP area at conferences such as LREC and CLNLP. She also enjoys working on open-source projects and is a contributor to the spaCy library. Duygu earned her undergraduate degree in Computer Engineering from METU, Ankara in 2010 and later earned her Master's degree in Mathematics from Bilkent University, Ankara in 2012. She is currently a senior engineer at German Autolabs with a focus on conversational AI for voice assistants. Originally from Istanbul, Duygu currently resides in Berlin, DE with her cute dog Adele.

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