While natural language processing (NLP) is largely used in search use cases, this book aims to inspire you to start using vectors to overcome equally important domain challenges like observability and cybersecurity. The chapters focus mainly on integrating vector search with Elastic to enhance not only their search but also observability and cybersecurity capabilities.
The book begins by teaching you about NLP and the functionality of Elastic in NLP processes. Next, you’ll delve into resource requirements and find out how vectors are stored in the dense-vector type along with specific page cache requirements for fast response times. As you advance, you’ll discover various tuning techniques and strategies to improve machine learning model deployment, including node scaling, configuration tuning, and load testing with Rally and Python. You’ll also cover techniques for vector search with images, fine-tuning models for improved performance, and the use of clip models for image similarity search in Elasticsearch. Finally, you’ll explore retrieval-augmented generation (RAG) and learn to integrate ChatGPT with Elasticsearch to leverage vectorized data, ELSER's capabilities, and RRF's refined search mechanism.
By the end of this NLP book, you’ll have all the necessary skills needed to implement and optimize vector search in your projects with Elastic.
publication date
2023-11-30
what you will learn
Optimize performance by harnessing the capabilities of vector search
Explore image vector search and its applications
Detect and mask personally identifiable information
Implement log prediction for next-generation observability
Use vector-based bot detection for cybersecurity
Visualize the vector space and explore Search.Next with Elastic
Implement a RAG-enhanced application using Streamlit
key features
Install, configure, and optimize the ChatGPT-Elasticsearch plugin with a focus on vector data * Learn how to load transformer models, generate vectors, and implement vector search with Elastic * Develop a practical understanding of vector search, including a review of current vector databases * Purchase of the print or Kindle book includes a free PDF eBook
approach
Throughout the book, readers will gain a solid understanding of the main notions and concepts of vector search. The journey will then progress to understanding how to apply, implement, manage, and optimize vector search in Elastic, with practical code examples provided. Finally, readers will explore real-life use cases that demonstrate the benefits and potential of vector search in Elastic.
audience
If you're a data professional with experience in Elastic observability, search, or cybersecurity and are looking to expand your knowledge of vector search, this book is for you. This book provides practical knowledge useful for search application owners, product managers, observability platform owners, and security operations center professionals. Experience in Python, using machine learning models, and data management will help you get the most out of this book.
short description
NLP for Practitioners with Elastic is a foundational guide that helps you get to grips with the fundamentals of vectors and embedding models. Using a hands-on approach, you’ll be able to enhance your search use case with vector search using Elastic. The book covers kNN search, NLP capabilities, and the current state of vector search databases.
subtitle
A toolkit for building NLP solutions for search, observability, and security using vector search
keywords
product management; product manager; Cyber security; Chat GPT; Ai/ml; Query Optimization; Hugging Face
Product ISBN
9781805121022
