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Desafío Neuronal: Verdadero o Falso

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Desafío Neuronal: Verdadero o Falso

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Verdadero o falso: redes neuronales.

Created by

Jeremmy Macías
Jeremmy Macías
Ecuador

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Desafío Neuronal: Verdadero o Falso
 

Desafío Neuronal: Verdadero o FalsoOnline version

Verdadero o falso: redes neuronales.

by Jeremmy Macías
1

El aprendizaje supervisado utiliza pares de entrada y salida para entrenar.

2

El pooling en redes neuronales convolucionales siempre reduce la precisión de la red.

3

El descenso por gradiente garantiza encontrar el óptimo global en redes profundas.

4

Las redes neuronales profundas tienen varias capas ocultas entre la entrada y la salida.

5

La normalización de datos no es necesaria para entrenar redes neuronales.

6

La retropropagación ajusta los pesos mediante cálculo de gradientes.

7

El entrenamiento de redes neuronales siempre termina en la misma solución global, sin importar la inicialización.

8

Las redes neuronales recurrentes solo funcionan con entradas fijas de longitud constante.

9

La función de activación introduce no linealidad en las neuronas.

10

Una red neuronal está formada por capas de neuronas artificiales.

 
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