New game
Download
Get Academic Plan
Share game
Integrate it into your platform

You can integrate the game into an LMS compatible with LTI 1.1 or LTI 1.3 such as Canvas, Moodle, or Blackboard. This way, the scores will be automatically saved into the platform’s gradebook.
Download
You have exceeded the maximum number of games you can integrate into Google Classroom with your current Plan.

To integrate as many games as you want in Google Classroom, you need an Academic Plan or a Commercial Plan.

You have exceeded the maximum number of games you can integrate into Microsoft Teams with your current Plan.

To integrate as many games as you want in Microsoft Teams, you need an Academic Plan or a Commercial Plan.

Downloading games is an exclusive feature for users with an Academic Plan or a Commercial Plan.

Get your Academic Plan or your Commercial Plan now and start integrating your games into your LMS, website or blog.

If you wish, you can download a demo game here and test its integration:

Desafío de Redes Neuronales

Yes or No

Played 1

About this activity

Reto rápido sobre redes neuronales.

Created by

Ecuador

Download the paper version to play

Make your own free game from our game creator
Compete against your friends to see who gets the best score in this game

Top Games

%
Anonymous
Anonymous
%
%
%
You have exceeded the maximum number of games you can print with your current Plan.

To print as many games as you want, you need an Academic Plan or a Commercial Plan.

Print your game
Desafío de Redes Neuronales
 

Desafío de Redes NeuronalesOnline version

Reto rápido sobre redes neuronales.

by Angel leonardo Aguirre barbech
1

La normalización por lotes reemplaza por completo la necesidad de funciones de activación no lineales.

2

Una red neuronal está formada por neuronas artificiales conectadas mediante pesos.

3

Un perceptrón simple, con una sola neurona, puede modelar cualquier relación no lineal.

4

El aprendizaje supervisado utiliza ejemplos etiquetados para ajustar los pesos.

5

La retropropagación se usa sin necesidad de calcular gradientes.

6

La función de activación introduce no linealidad en la salida de una neurona.

7

Una red neuronal profunda se define por tener más de una capa oculta.

8

El descenso del gradiente es un algoritmo típico para optimizar los pesos.

9

Softmax se aplica en la capa oculta para normalizar las salidas entre neuronas.

10

El pooling max aumenta la resolución de la imagen al extraer valores máximos.

Are you sure you want to leave the page?

If you leave the page, you will lose your game progress.