Este curso se centrará en la optimización de Redes Neuronales Profundas, cambiando la idea de que todo el proceso es una “caja negra”.
What you'll 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.
Implementar una red neuronal en TensorFlow.
Skills you'll gain
- Implementar una red neuronal en TensorFlow.
- Utilizar eficazmente los "trucos" comunes de la red neuronal incluida la inicialización la regularización de L2 los dropout y la normalización por lotes (Batch)
- Implementar y aplicar una variedad de algoritmos de optimización.
- Comprender las mejores prácticas de la industria para crear aplicaciones de aprendizaje profundo.
Details to know
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There are 3 modules in this course
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.
What's included
7 videos3 readings1 assignment1 ungraded lab
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.
What's included
5 videos1 assignment1 ungraded lab
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
What's included
4 videos1 programming assignment
Offered by
Recommended if you're interested in Networking
Google Cloud
Arizona State University
Universidad Nacional Autónoma de México
Universidad Nacional Autónoma de México
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