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Bo Wang - Neural Search - From Prototype to Production with Jina: Build deep learning–powered search systems that you can deploy and manage with ease

Here you can read online Bo Wang - Neural Search - From Prototype to Production with Jina: Build deep learning–powered search systems that you can deploy and manage with ease full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2022, publisher: Packt Publishing, genre: Computer. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

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Bo Wang Neural Search - From Prototype to Production with Jina: Build deep learning–powered search systems that you can deploy and manage with ease

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Implement neural search systems on the cloud by leveraging 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 knowledge of Jina for neural search
Book Description

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 learningpowered 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, youll 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, youll be able to make the most of Jinas 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 search systems with different modalities
  • Uncover the capabilities of Jina with the help of practical examples
Who this book is for

If you are a machine learning, deep learning, or artificial intelligence 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 perfect 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
  1. Neural Networks for Neural Search
  2. Introducing Foundations of Vector Representation
  3. System Design and Engineering Challenges
  4. Learning Jinas Basics
  5. Multiple Search Modalities
  6. Basic Practical Examples with Jina
  7. Exploring Advanced Use Cases of Jina

Bo Wang: author's other books


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Neural Search From Prototype to Production with Jina Build deep learningpowered - photo 1
Neural Search From Prototype to Production with Jina

Build deep learningpowered search systems that you can deploy and manage with ease

Jina AI

Bo Wang

Cristian Mitroi

Feng Wang

Shubham Saboo

Susana Guzmn

BIRMINGHAMMUMBAI Neural Search From Prototype to Production with Jina Copyright - photo 2

BIRMINGHAMMUMBAI

Neural Search From Prototype to Production with Jina

Copyright 2022 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Kunal Chaudhari

Publishing Product Manager: Dhruv Jagdish Kataria

Senior Editor: Nisha Cleetus

Content Development Editor: Nithya Sadanandan

Technical Editor: Pradeep Sahu

Copy Editor: Safis Editing

Project Coordinator: Ajesh Devavaram

Proofreader: Safis Editing

Indexer: Tejal Daruwale Soni

Production Designer: Shankar Kalbhor

Marketing Coordinator: Abeer Riyaz Dawe

Business Development Executive: Surya Srivastav

First published: September 2022

Production reference: 1160922

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80181-682-3

www.packt.com

Contributors
About the authors

Bo Wang is a machine learning engineer at Jina AI. He has a background in computer science, especially interested in the field of information retrieval. In the past years, he has been conducting research and engineering work on search intent classification, search result diversification, content-based image retrieval, and neural information retrieval. At Jina AI, Bo is working on developing a platform for automatically improving search quality with deep learning. In his spare time, he likes to play with his cats, watch anime, and play mobile games.

This book is a joint effort between Jina AI and Packt Publishing. I appreciate everyone who organized and participated in writing this unique book. Thank you, Bing, for giving us such a great opportunity to share our learnings with others, and thanks to all the co-authors, Shubham, Susana, Feng, Alex Cureton-Griffiths, and Cristian, for their hard work. I would also like to share my gratitude to Zizhen Wang for helping me with Chapter 1 and Chapter 2 of the book.

I feel honored to have worked with a professional editing team, including Nithya Sadanandan and Prajakta Naik. Your feedback always helped me better convey my thoughts with great clarity.

Cristian Mitroi is a machine learning engineer with a wide breadth of experience in full stack, from infrastructure to model iteration and deployment. His background is based in linguistics, which led to him focusing on NLP. He also enjoys, and has experience in, teaching and interacting with the community, and has given workshops at various events. In his spare time, he performs improv comedy and organizes too many pen-and-paper role-playing games.

I would like to thank the entire Jina AI team for providing a great working environment and being massively supportive and helpful. A special thank you goes to Han, for laying the foundation. I would also like to thank my mentor, Max, for all the memorable insights. Last but not least, I want to thank my supportive girlfriend, for bearing with my nerdy monologues.

Feng Wang is a machine learning engineer at Jina AI. He received his Ph.D. from the department of computer science at the Hong Kong Baptist University in 2018. He has been a full-time R&D engineer for the past few years, and his interests include data mining and artificial intelligence, with a particular focus on natural language processing, multi-modal representation learning, and recommender systems. In his spare time, he likes climbing, hiking, and playing mobile games.

I would like to thank everyone who helped me with the writing process. Its been a great honor to have this chance to share my learnings of neural search with the world. I am grateful to have worked with my brilliant co-authors, Bo, Susana, Alex Cureton-Griffiths, Shubham, and Christian. Thanks to our professional editors, Nithya Sadanandan and Prajakta Naik. Their work has been a great help in making this book available to the world. I would also like to thank my wife, Ting Wang, for being there for me. She acted as a catalyst for me to write this book.

Shubham Saboo has taken on multiple roles, from a data scientist to an AI evangelist, at renowned firms across the globe, where he was involved in building organization-wide data strategies and technology infrastructure to create and scale data teams from scratch. His work as an AI evangelist has led him to build communities and reach out to a broader audience to foster the exchange of ideas and thoughts in the burgeoning field of AI. As part of his passion for learning new things and sharing knowledge with the community, he writes technical blogs on the advancements in AI and its economic implications. In his spare time, you can find him traveling the world, which enables him to immerse himself in different cultures and refine his worldview.

I would like to acknowledge Han Xiao, for coming up with the Jina framework to make neural search accessible to all, and Bing He, for giving me the opportunity to write this book. Im grateful to have worked with my brilliant co-authors, Bo, Susana, Alex Cureton-Griffiths, Feng, and Christian, who helped me throughout the writing process and deepened my understanding of neural search. Huge thanks to the editors, Nithya Sadanandan and Prajakta Naik, who did a great job at shaping the book into its final form.

Id also like to thank my mom, Gayatri, who always believed in me irrespective of the odds. My love, Gargi, for being there for me at every step and making this journey of writing the book a blissful experience.

Susana Guzmn is the product manager at Jina AI. She has a background in computer science and for several years was working at different firms as a software developer with a focus on computer vision, working with both C++ and Python. She has a big interest in open source, which was what led her to Jina, where she started as a software engineer for 1 year until she got a clear overview of the product, which made her make the switch from engineering to PM. In her spare time, she likes to cook food from different cuisines around the world, looking for her new favorite dish.

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