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Vector Search for Practitioners with Elastic

You're reading from  Vector Search for Practitioners with Elastic

Product type Book
Published in Nov 2023
Publisher Packt
ISBN-13 9781805121022
Pages 240 pages
Edition 1st Edition
Languages
Authors (2):
Bahaaldine Azarmi Bahaaldine Azarmi
Profile icon Bahaaldine Azarmi
Jeff Vestal Jeff Vestal
Profile icon Jeff Vestal
View More author details

Table of Contents (17) Chapters

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