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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

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781800563353
Length 356 pages
Edition 1st Edition
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Author (1):
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Duygu Altınok Duygu Altınok
Author Profile Icon Duygu Altınok
Duygu Altınok
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Toc

Table of Contents (15) Chapters Close

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

Summary

Congratulations! You have made it to the end of a very intense chapter!

In this chapter, you learned how to generate a complete semantic parse of utterances. First, you made a discovery on your dataset to get insights about the dataset analytics. Then, you learned to extract entities with two different techniques – with spaCy Matcher and by walking on the dependency tree. Next, you learned different ways of performing intent recognition by analyzing the sentence structure. Finally, you put all the information together to generate a semantic parse.

In the next chapters, we will shift toward more machine learning methods. The next section concerns how to train spaCy NLP pipeline components on your own data. Let's move ahead and customize spaCy for ourselves!

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