Reinforcement Learning and Deep RL Python Theory and Projects - DNN Architecture Exercise

Reinforcement Learning and Deep RL Python Theory and Projects - DNN Architecture Exercise

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial explains the concept of parameters or weights in a deep neural network. It uses a simple example with three features and two layers to illustrate the structure of a neural network. The tutorial details the number of neurons in each layer and emphasizes the importance of counting the total number of weights, which are the parameters of the network. A hint is provided to focus on an extra edge when calculating parameters, with a promise to reveal the solution in the next video.

Read more

5 questions

Show all answers

1.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the features mentioned in the example of the deep neural network?

Evaluate responses using AI:

OFF

2.

OPEN ENDED QUESTION

3 mins • 1 pt

How many layers are there in the described neural network, and how many neurons are in each layer?

Evaluate responses using AI:

OFF

3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of weights in the neurons of a neural network?

Evaluate responses using AI:

OFF

4.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the goal when counting the total number of weights in a neural network?

Evaluate responses using AI:

OFF

5.

OPEN ENDED QUESTION

3 mins • 1 pt

What hint is provided for computing the number of parameters in the neural network?

Evaluate responses using AI:

OFF

Access all questions and much more by creating a free account

Create resources

Host any resource

Get auto-graded reports

Google

Continue with Google

Email

Continue with Email

Classlink

Continue with Classlink

Clever

Continue with Clever

or continue with

Microsoft

Microsoft

Apple

Apple

Others

Others

Already have an account?