Implement neural search systems on the cloud by mastering Jina design patterns.
Key Features
- Identify the different search techniques and discover applications of neural search.
- Gain a solid understanding of vector representation and apply your knowledge in neural search.
- Unlock deeper levels of understanding of Jina for neural search.
Book Description
Search is a big part of the tech ecosystem that keeps growing every day. Traditional search, however, has limitations that are hard to overcome because of the way it is designed. A Neural Search is a novel approach that uses the power of ML to retrieve information using vector embeddings as first-class citizens, enabling new possibilities to improve the results obtained through traditional search.
Although neural search is a powerful tool, it is new and finetuning it can be tedious as it requires you to understand the several components on which it relies. Jina fills this gap by providing an infrastructure that reduces the time and complexity involved in creating deep-learning- powered search engines. With this book, you'll learn the fundamentals of neural search, its strengths and weaknesses, as well as how to use Jina to build a search engine.
Complete with step-by-step explanations, practical examples, and self-assessment questions, you'll become well versed with the basics of neural -search and core Jina concepts, and apply this knowledge to build your own search engine.
By the end of this book, you'll be able to make the most of Jina's neural search design patterns to build an end-to-end search solution for any modality.
What you will learn
- Understand how neural search and legacy search work.
- Grasp the machine learning and math fundamentals needed for neural search.
- Get to grips with the foundation of vector representation.
- Explore the basic components of Jina.
- Analyze the search system with different modalities.
- Uncover the capabilities of Jina with the help of practical examples.
Who This Book Is For
If you are an ML, DL, or AI engineer interested in building a search system of any kind (text, QA, image, audio, PDF, 3D models, or others) using modern software architecture, this book is for you.
This book is excellent for Python engineers who are interested in building a search system (of any kind) using state-of-the-art deep learning techniques.
Table of Contents
- Intro to Neural Search Fundamentals
- Foundations of Vector Representation
- System Design of a Search System and engineering challenges
- Jina Basic Components
- Multiple Search Modalities
- Basic Practical examples with Jina
- Advanced Practical examples with Jina
