Summary
Deep Learning for Search teaches you how to improve the effectiveness of your search by implementing neural network-based techniques. By the time you're finished with the book, you'll be ready to build amazing search engines that deliver the results your users need and that get better as time goes on!
Foreword by Chris Mattmann.
About the Technology
Deep learning handles the toughest search challenges, including imprecise search terms, badly indexed data, and retrieving images with minimal metadata. And with modern tools like DL4J and TensorFlow, you can apply powerful DL techniques without a deep background in data science or natural language processing (NLP). This book will show you how.
About the Book
Deep Learning for Search teaches you to improve your search results with neural networks. You'll review how DL relates to search basics like indexing and ranking. Then, you'll walk through in-depth examples to upgrade your search with DL techniques using Apache Lucene and Deeplearning4j. As the book progresses, you'll explore advanced topics like searching through images, translating user queries, and designing search engines that improve as they learn!
What's inside
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Tommaso Teofili is a software engineer at Adobe Systems with a passion for open source and artificial intelligence. He is a long-time member of the Apache Software Foundation, where he contributes to many projects on topics like information retrieval, natural language processing, and distributed computing.
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