Deep Learning CNN Convolutional Neural Networks with Python - Calculating Number of Weights of DNN Solution

Deep Learning CNN Convolutional Neural Networks with Python - Calculating Number of Weights of DNN Solution

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

Created by

Quizizz Content

FREE Resource

The video tutorial explains the structure of a neural network's input hidden layer, detailing the number of inputs and the calculation of trainable parameters. It covers the breakdown of parameters for different neurons and concludes with a total count of 35 trainable parameters.

Read more

5 questions

Show all answers

1.

OPEN ENDED QUESTION

3 mins • 1 pt

How many inputs does the first hidden layer have?

Evaluate responses using AI:

OFF

2.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the total number of inputs coming from the input layer?

Evaluate responses using AI:

OFF

3.

OPEN ENDED QUESTION

3 mins • 1 pt

How many inputs do three of the neurons have?

Evaluate responses using AI:

OFF

4.

OPEN ENDED QUESTION

3 mins • 1 pt

How many trainable parameters does the last neuron have?

Evaluate responses using AI:

OFF

5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the total number of trainable parameters calculated?

Evaluate responses using AI:

OFF