Deep Learning for Search

by Tommaso Teofili

Deep Learning for Search teaches you how to improve the effectiveness of your search by implementing neural network-based techniques. You'll start with an overview of information retrieval principles, like indexing, searching, and ranking, as well as a fast indoctrination into deep learning. Then, you'll move through in-depth examples as you gain an understanding of how to improve typical search tasks, such as relevance, with the help of Apache Lucene and Deeplearning4j. The book wraps up with a look at advanced problems, like searching through images and translating user queries. By the time you're finished, you'll be ready to build amazing search engines that deliver the results your users need and get better as time goes on!

Genres: Computer Science, Artificial Intelligence

325 pages, Paperback

Published July 1, 2018

Reviews

[Rick Sam · Rating 4 out of 5]

Good Introduction work for Information Retrieval Search.

Although - could not find excruciating details about limitations for each method.

Eg: Why BM25? Why not Word2Vec

Why this method works?

What is the limitation of this method?

How can I create this method from scratch?

At-least conceptually in my head

Recommended for everyone

Deus Vult,
Gottfried

[Xianshun Chen · Rating 2 out of 5]

disappointed after buying and reading the book. I think the book is not up to date with the latest development in the NLP and search ML. It might be good for some novice joining the field but definitely lacks the depth for someone which need to push the edge of the field.

[Zdeněk Tisoň · Rating 5 out of 5]

This book is really amazing. It is unique on the market. I have learned how to combine Lucene based searching with Deep learning. Great job Tommaso