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Future of Analytics

As enterprise adoption of AI and machine learning software becomes more commonplace, what does your company need to know to invest wisely in these technologies? In this detailed report, authors Rafael Coss, Dan Darnell, and Patrick Hall provide valuable information to help managers and practitioners...

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Detalles Bibliográficos
Autor principal: Coss, Rafael
Otros Autores: Darnell, Dan, Hall, Patrick
Formato: Electrónico eBook
Idioma:Indeterminado
Publicado: [S.l.] : O'Reilly Media, Inc., 2020.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a As enterprise adoption of AI and machine learning software becomes more commonplace, what does your company need to know to invest wisely in these technologies? In this detailed report, authors Rafael Coss, Dan Darnell, and Patrick Hall provide valuable information to help managers and practitioners make sound decisions for your organization in this commercial landscape. Analytics adoption has driven a wave of digital transformation across industries, but many projects face significant drawbacks. Through the course of this report, you'll examine two of these issues: how the lack of involvement and access by domain experts and end users causes projects to lose focus and why predictive models often end up as services rather than part of new or existing applications. The entire report covers a breadth of topics that include: The converging world of analytics: an up-to-date overview of the AI, ML, and analytics software ecosystem Modern AI applications: anatomy, key components, and detailed examples of the most promising use cases Adoption challenges for next-gen analytics: including organizational, infrastructure, modeling, governance, operational, and social issues Case studies: real-world perspectives from users of modern AI and ML software. 
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