Deep Learning CNN Convolutional Neural Networks with Python - Decision Boundary in DNN

Deep Learning CNN Convolutional Neural Networks with Python - Decision Boundary in DNN

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial explains the concept of decision boundaries in neural networks. It describes how each neuron acts as a computational unit representing a hyperplane in the input space. In a two-dimensional space, neurons represent lines that can classify data points into different classes. By increasing the number of neurons, the decision boundary can be approximated more smoothly. In higher-dimensional spaces, neurons represent hyperplanes, and their intersections form complex decision boundaries.

Read more

3 questions

Show all answers

1.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe how increasing the number of neurons affects the smoothness of the decision boundary.

Evaluate responses using AI:

OFF

2.

OPEN ENDED QUESTION

3 mins • 1 pt

What happens to the representation of a neuron when the input space has more than two dimensions?

Evaluate responses using AI:

OFF

3.

OPEN ENDED QUESTION

3 mins • 1 pt

How can complex decision boundaries be achieved in higher-dimensional spaces?

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?