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Vector Search for Practitioners with Elastic

You're reading from   Vector Search for Practitioners with Elastic A toolkit for building NLP solutions for search, observability, and security using vector search

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781805121022
Length 240 pages
Edition 1st Edition
Languages
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Authors (2):
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Jeff Vestal Jeff Vestal
Author Profile Icon Jeff Vestal
Jeff Vestal
Bahaaldine Azarmi Bahaaldine Azarmi
Author Profile Icon Bahaaldine Azarmi
Bahaaldine Azarmi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1:Fundamentals of Vector Search
2. Chapter 1: Introduction to Vectors and Embeddings FREE CHAPTER 3. Chapter 2: Getting Started with Vector Search in Elastic 4. Part 2: Advanced Applications and Performance Optimization
5. Chapter 3: Model Management and Vector Considerations in Elastic 6. Chapter 4: Performance Tuning – Working with Data 7. Part 3: Specialized Use Cases
8. Chapter 5: Image Search 9. Chapter 6: Redacting Personal Identifiable Information Using Elasticsearch 10. Chapter 7: Next Generation of Observability Powered by Vectors 11. Chapter 8: The Power of Vectors and Embedding in Bolstering Cybersecurity 12. Part 4: Innovative Integrations and Future Directions
13. Chapter 9: Retrieval Augmented Generation with Elastic 14. Chapter 10: Building an Elastic Plugin for ChatGPT 15. Index 16. Other Books You May Enjoy

Summary

In this chapter, we introduced the opportunity to use a pre-trained model called ELSER, which leverages vectors without users having to manage the vectorization process. It’s an out-of-the-box model that generates immediate value from a semantic search perspective. We applied ELSER to the challenge of phishing attacks with the task in mind being to limit the impact of such attacks. You should now be able to build your pipeline to load data in Elasticsearch and start building applications that leverage ELSER, whether in cybersecurity or beyond.

In the next chapter, we are going to go a step further in leveraging vectors by building a retrieval augmented generation application.

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