October 2024
Intermediate to advanced
268 pages
6h 56m
Spanish
Content preview from Escalando Python con Ray
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Capítulo 8. Flujos de trabajo de rayos
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Las aplicaciones modernas y de la vida real en una amplia gama de dominios suelen ser una combinación de múltiples pasos interdependientes. Por ejemplo, en los flujos de trabajo de IA/ML, las cargas de trabajo de entrenamiento requieren múltiples pasos para la limpieza, el equilibrio y el aumento de datos, mientras que el servicio de modelos a menudo incluye muchas subtareas y la integración con procesos empresariales de larga duración. Los distintos pasos de los flujos de trabajo pueden depender de múltiples flujos ascendentes y a veces requieren distintas herramientas de escalado.
Las bibliotecas informáticas para la gestión de flujos de trabajo se remontan a hace más de 25 años, y están surgiendo nuevas herramientas centradas en la IA/ML. Las especificaciones de los flujos de trabajo van desde interfaces gráficas de usuario a formatos personalizados, pasando por YAML Ain't Markup Language (YAML) y Extensible Markup Language (XML), y bibliotecas en lenguajes de programación completos. Especificar los flujos de trabajo en código te permite utilizar herramientas generales de programación, como el control de código fuente para el versionado y la colaboración.
En este capítulo, aprenderás los fundamentos de la implementación de los Flujos de Trabajo de Ray y algunos ejemplos sencillos ...
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