Coursera

Optimización de Redes Neuronales Profundas (Coursera)

Offered by Universidad Austral,

Este curso se centrará en la optimización de Redes Neuronales Profundas, cambiando la idea de que todo el proceso es una “caja negra”. Comprenderá qué impulsa el rendimiento y podrá obtener mejores resultados de manera más sistemática. Entenderá cómo optimizar los principales Hiperparámetros y su implementación. Además, aprenderá nuevos conceptos útiles para el entrenamiento de las redes como los mini-batch y las regularizaciones. También, aprenderá a implementar una red neuronal utilizando TensorFlow

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What You Will Learn

Utilizar eficazmente los "trucos" comunes de la red neuronal
Comprender las mejores prácticas de la industria para crear aplicaciones de aprendizaje profundo.
Implementar y aplicar una variedad de algoritmos de optimización.

Syllabus

WEEK 1
Aspectos prácticos del aprendizaje profundo
Se estudiará cómo configurar su aplicación de aprendizaje automático, separando los sets de entrenamiento y testeo. Se entenderá que es la regularización en una red neuronal y cómo definir el problema para poder optimizarlo.

WEEK 2
Algoritmos de Optimización
Se estudiarán los distintos métodos de optimización que se pueden utilizar en el entrenamiento de redes neuronales profundas. Además, se analizarán las ventajas de trabajar con minibatches para acelerar el proceso y los beneficios de aplicar una diminución progresiva a la tasa de aprendizaje.

WEEK 3
Ajuste de Hiperparámetros, Normalización por lotes e implementación en Tensorflow
Se aprenderán las principales técnicas y opciones en el ajuste de Hiperparámetros, la normalización por lotes y se introducirá la librería Tensorflow para la implementación de redes neuronales en Python

Go to Class

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