En este curso, aprenderá de los ingenieros y capacitadores de AA que trabajan en el desarrollo de vanguardia de las canalizaciones de AA en Google Cloud. En los primeros módulos, se abordará TensorFlow Extended (o TFX), la plataforma de aprendizaje automático de producción de Google basada en TensorFlow para la administración de canalizaciones y metadatos de AA. Aprenderá sobre los componentes y la organización de las canalizaciones con TFX. También aprenderá cómo automatizar su canalización mediante la integración y la implementación continuas, y cómo administrar ML Metadata. Luego, cambiaremos el enfoque para analizar cómo podemos automatizar y volver a usar las canalizaciones de AA en múltiples frameworks de AA, como TensorFlow, PyTorch, scikit-learn y XGBoost. Además, aprenderá a usar Cloud Composer, otra herramienta de Google Cloud, para organizar sus canalizaciones de entrenamiento continuo. Por último, aprenderá a usar MLflow para administrar el ciclo de vida completo del aprendizaje automático.
ML Pipelines on Google Cloud en Español
ML Pipelines on Google Cloud en EspañolGoogle Cloud
About this Course
What you will learn
Desarrolle una comprensión general de los componentes de canalizaciones estándar de TFX.
Aprenda a usar un contexto interactivo de TFX para desarrollar prototipos de canalizaciones de TFX.
Entrenamiento continuo con modelos de TensorFlow, PyTorch, XGBoost y scikit-learn con KubeFlow y AI Platform Pipelines
Realice un entrenamiento continuo con Composer y MLFlow
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Syllabus - What you will learn from this course
En este módulo, se describe la organización del curso
Introducción a las canalizaciones de TFX
En este módulo, se presenta TensorFlow Extended (o TFX) y se abordan los conceptos y componentes de TFX
Organización de las canalizaciones con TFX
Esto es lo que abordaremos en este módulo:
Componentes personalizados y CI/CD para canalizaciones de TFX
Esto es lo que abordaremos en este módulo:
ML Metadatos con TFX
Este módulo trata sobre el uso de metadatos de TFX para la administración de artefactos
Entrenamiento continuo con múltiples SDK, Kubeflow y AI Platform Pipelines
En este módulo, se aborda el entrenamiento continuo con múltiples SDK, Kubeflow y AI Platform Pipelines
Entrenamiento continuo con Cloud Composer
En este módulo, se aborda el entrenamiento continuo con Cloud Composer
Canalizaciones de AA con MLflow
En este módulo, se presenta MLflow y sus componentes
En este módulo, se describe un resumen del curso
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Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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Last Updated: September 1, 2015
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