September 2024
Intermediate to advanced
392 pages
10h 22m
Spanish
Content preview from Inteligencia empresarial basada en IA
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Capítulo 2. Del BI a la Inteligencia para la Toma de Decisiones: Evaluar la viabilidad de los proyectos de IA
Este trabajo se ha traducido utilizando IA. Agradecemos tus opiniones y comentarios: translation-feedback@oreilly.com
En el capítulo anterior, aprendiste cómo las capacidades de ML podían impulsar el impacto empresarial. Pero para crear una hoja de ruta de casos de uso priorizados y tomar una decisión informada sobre qué casos de uso perseguir prioritariamente, tenemos que considerar otra dimensión de los criterios: la viabilidad.
Este capítulo profundiza mucho más en los fundamentos del ML para que puedas evaluar la complejidad y la viabilidad general de un determinado caso de uso de la IA. Exploraremos la viabilidad basándonos en tres temas principales: datos, infraestructura/arquitectura y ética. Como resultado, podrás crear la primera versión de tu hoja de ruta de casos de uso de BI potenciados por IA.
Dar prioridad a los datos
Los proyectos de IA requieren una mentalidad diferente a la de los proyectos clásicos de BI. La mayoría de los proyectos de BI se realizan de forma relativamente sencilla, a menudo siguiendo el modelo tradicional en cascada de: define la métrica que quieres mostrar, diseña el modelo de datos, integra los datos y asegúrate de que funciona (lo que a menudo es bastante difícil). Iterar si es necesario. Trabajo hecho.
La principal diferencia en los proyectos de IA es que -incluso en circunstancias ideales- el resultado es muy incierto. Sencillamente, ...
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