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Getting started with artificial intelligence : a practical guide to building enterprise applications /
Artificial intelligence techniques are becoming a fundamental component of business growth across a wide range of industries. Enterprise technologies that automate and detect patterns can augment human expertise, empowering both employees and applications to make richer, more data-driven decisions....
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media,
[2017]
|
| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Markiewicz, Tom, |e author. | |
| 245 | 1 | 0 | |a Getting started with artificial intelligence : |b a practical guide to building enterprise applications / |c Tom Markiewicz and Josh Zheng. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, |c [2017] | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Online resource; title from title page (Safari, viewed January 8, 2019). | |
| 504 | |a Includes bibliographical references. | ||
| 520 | |a Artificial intelligence techniques are becoming a fundamental component of business growth across a wide range of industries. Enterprise technologies that automate and detect patterns can augment human expertise, empowering both employees and applications to make richer, more data-driven decisions. Complete with case studies, implementation examples, and a survey of the current landscape, this book serves as an ideal starting point for your journey into enterprise AI. As a developer tasked with building enterprise-level AI applications, you're looking to learn about the tools and techniques that will help you get the job done. In this book, authors Tom Markiewicz and Josh Zheng--developer advocates for IBM Watson--explore three of the more common uses for AI in the enterprise: natural language processing (NLP), computer vision, and chatbots. You'll also learn methods for creating a data pipeline that forms the backbone for building these applications. Explore why NLP is the key to mining unstructured data in emails, articles, blog posts, customer support discussions, and other documents Gain practical tips for building chatbots, and learn how these applications are used in the customer support and e-commerce industries Examine capabilities that computer vision brings to your applications, including image classification and tagging Get a high-level guide to data pipelines--the backbone of your AI applications. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Application software |x Development. | |
| 650 | 0 | |a Natural language processing (Computer science) | |
| 650 | 0 | |a Information technology |x Technological innovations. | |
| 650 | 0 | |a Communication |x Technological innovations. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Logiciels d'application |x Développement. | |
| 650 | 6 | |a Traitement automatique des langues naturelles. | |
| 650 | 6 | |a Technologies de l'information et de la communication. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Application software |x Development |2 fast | |
| 650 | 7 | |a Artificial intelligence |2 fast | |
| 650 | 7 | |a Information technology |x Technological innovations |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Natural language processing (Computer science) |2 fast | |
| 700 | 1 | |a Zheng, Josh, |e author. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781492027805/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||