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Neural Search - From Prototype to Production with Jina
By :

Neural Search - From Prototype to Production with Jina
By:
Overview of this book
Search is a big and ever-growing part of the tech ecosystem. Traditional search, however, has limitations that are hard to overcome because of the way it is designed. Neural search is a novel approach that uses the power of machine learning to retrieve information using vector embeddings as first-class citizens, opening up new possibilities of improving 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. This book will enable you to learn the fundamentals of neural networks for neural search, its strengths and weaknesses, as well as how to use Jina to build a search engine. With the help of 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 learn to apply this knowledge to build your own search engine.
By the end of this deep learning 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.
Table of Contents (13 chapters)
Preface
Part 1: Introduction to Neural Search Fundamentals
Chapter 1: Neural Networks for Neural Search
Chapter 2: Introducing Foundations of Vector Representation
Chapter 3: System Design and Engineering Challenges
Part 2: Introduction to Jina Fundamentals
Chapter 4: Learning Jina’s Basics
Chapter 5: Multiple Search Modalities
Part 3: How to Use Jina for Neural Search
Chapter 6: Building Practical Examples with Jina
Chapter 7: Exploring Advanced Use Cases of Jina
Index
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