Résumé
Description
Deep Learning for Search teaches readers how to leverage neural networks, NLP, and deep learning techniques to improve search performance.
Deep Learning for Search teaches readers how to improve the effectiveness of your search by implementing neural network-based techniques. By the time their finished, they'll be ready to build amazing search engines that deliver the results your users need and get better as time goes on!
Key Features
* Search with recommendations
* Accurate and relevant rankings of search results
* Generating suitable synonyms
Audience
Written for developers comfortable with Java or a similar language. No experience with deep learning or NLP needed.
About the Technology
Using deep learning and neural networks are the perfect way to create better search results, letting users fine tune what their search engines display, help speed up the results, and let them build a profile of their customers that let them find what they need every single time.
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.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Mannings publ. |
| Auteur(s) | Tommaso Teofili |
| Parution | 27/06/2019 |
| Nb. de pages | 328 |
| EAN13 | 9781617294792 |
Avantages Eyrolles.com
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