En este curso, se explica cómo diseñar y crear una canalización de datos de entrada de TensorFlow, cómo crear modelos de AA con TensorFlow y Keras, cómo mejorar la precisión de los modelos de AA, cómo escribir modelos de AA para uso escalado y cómo escribir modelos de AA especializados.
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TensorFlow on Google Cloud - Español
What you'll learn
Crear modelos de aprendizaje automático de TensorFlow y Keras, y describir sus componentes clave
Usar la biblioteca de tf.data para manipular datos y grandes conjuntos de datos
Usar las APIs secuencial y funcional de Keras para crear modelos simples y avanzados
Entrenar, implementar y llevar a producción modelos de AA a gran escala con Vertex AI
Details to know
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There are 6 modules in this course
En este módulo, se brinda una descripción general del curso y sus objetivos.
What's included
1 video
En este módulo, se presenta el marco de trabajo de TensorFlow y se ofrece una vista previa de sus componentes principales, así como de la jerarquía general de las API.
What's included
4 videos1 reading1 quiz
Los datos son un componente esencial de los modelos de aprendizaje automático. Recopilar los datos correctos no es suficiente. También es necesario asegurarse de implementar los procesos adecuados para limpiar, analizar y transformar los datos según sea necesario, de modo que el modelo pueda captar tantos indicadores como sea posible a partir de esos datos. En este módulo, analizamos el entrenamiento con grandes conjuntos de datos mediante tf.data, el trabajo con archivos en la memoria y cómo preparar los datos para el entrenamiento. Después, analizamos las incorporaciones y terminamos con una descripción general del escalamiento de datos con capas de procesamiento previo de tf.keras.
What's included
10 videos1 reading1 quiz2 app items
En este módulo, analizamos las funciones de activación y cómo se las necesita para permitir que las redes neuronales profundas registren los aspectos no lineales de los datos. Después, se ofrece una descripción general de las redes neuronales profundas con las APIs secuencial y funcional de Keras. A continuación, describimos la subclasificación de modelos, que ofrece mayor flexibilidad para la creación de modelos. El módulo finaliza con una lección sobre regularización.
What's included
10 videos1 reading1 quiz2 app items
En este módulo, describimos cómo entrenar modelos de TensorFlow a gran escala con Vertex AI.
What's included
3 videos1 reading1 quiz1 app item
Este módulo es un resumen del curso TensorFlow on Google Cloud.
What's included
4 readings
Instructor
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