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Amazon verified reviews

Abhijit Jan 15, 2023

The book shines in several aspects like:■ It provides a comprehensive overview of classic to emerging topics in NLP, complemented with stand-alone hands on reusable code recipies for each concept.■ The book presents a survey of several relevant algorithms with synopsis. This can be useful to guide your use-case specific research.■ The book has used JINA as framework to illustrate various illustrative examples on search and there are tutorials to give you a jumpstart with JINA.■ Beyond text the book also delves into into multi-modal search (image and audio search). The book does reasonably good in marrying the whole subject within the fundaental underpinnings of NLP.■ In future editions, I would like to see more coverage on transformers/BERT/SBERT based search systems.

Amazon Verified review

Daniel Armstrong Feb 08, 2023

If you are interested in learning more about Neural Search or Jina I think this book would be a great addition to your library. I really enjoyed the author's thought and explanations, like their explanations of Neural search, vector representations and LSH.Over the years I have used used several different methods and libraries, for neural search. Both for research and in production. I had very high hopes for Jina especially using clip and subindicies (not covered in book), subindicies allow you to have multiple documents ( images, text, audio, etc) under that same parents. If your interested you can fine more information in the jina docs.Jina attempts to simplify neural search projects by doing a lot of the work for you, wrapping everything in very nice objects like docarrays. These objects makes Jina great for beginners or software engineers, but I found it challenging to customize when the defaults didn't meet my needs.I am not a huge fan of Jina Flow, which attempts to wrap everything together into an easy to use flow, it could be because of my lack of understanding but it just didn't seem worth the hassle, since I can make all the pieces outside of Jina flows or jina.I have high hopes for future of Jina, it could be a great tool for so many projects. That is why I would highly recommend this book for anyone interested in the subject. I would have like to see more examples of how you can customize Jina, outside of Jina flows. I would have also loved to learn more about vector databases, both inside and outside of Jina.

Yiqiao Yin Nov 16, 2022

Neural search is a big thing. I really enjoy reading this book and it covers an ever-growing industry nationwide. The traditional neural search algorithms have pros and cons, and that's where this book starts with. Then it dives into the math and provides a technical overview of the major painspot and where things can be improved before it covers the proposed pipeline using Jina AI platform.> The book provides powerful tools to finetune tedious machines and each component it relies on. The proposed platform will also help to fill in the gap.> The book helps you understand the fundamentals of neural search algorithms. Not only that the book also outlines the strengths and weaknesses.> The book also allowed me to become familiar with using the Jina AI code blocks which is highly modularized and easily deployable.

Steven Fernandes Dec 12, 2022

The book is divided into three parts and introduces Neural Search with Jina. The first part introduces Neural Search, including the foundation of vector representation. The second part is my favorite which introduces the fundamentals of Jina. It includes how to encode multimodal documents and cross-model searches. The final part shows how to implement Jina for Neural Search. Including fashion image search and concurrent querying and indexing of data.Overall the book is around 175 pages and forms a good introduction. I would recommend referring to other Packt books for an advanced and detailed understanding of Jina

Community Prism Pvt Ltd Dec 06, 2022

Great book for beginners who wish to setup production level neural search from scratch.Best part is it takes the reader from introduction to traditional neural search and whole evolution till state of the art algorithms.Moreover using jina.ai framework it gets way easy to setup, develop and scale.

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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