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About this book


Deep Learning for Search is a practical book about how to use (deep) neural networks to help build effective search engines. This book examines several components of a search engine, providing insights on how they work and guidance on how neural networks can be used in each context. Emphasis is given to practical, example-driven explanations of search and deep learning techniques, most of which are accompanied by code. At the same time, references to relevant research papers are provided where applicable to encourage you to read more and deepen your knowledge on specific topics. Neural network and search-specific topics are explained throughout the book as you read about them.

After reading this book, you’ll have a solid understanding of the main challenges related to search engines, how they are commonly addressed, and what deep learning can do to help. You’ll gain a solid understanding of several different deep learning techniques and where they fit in the context of search. You’ll get to know the Lucene and Deeplearning4j libraries well. In addition, you’ll develop a practical attitude toward testing the effectiveness of neural networks (rather than viewing them as magic) and measuring their costs and benefits.

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