Practice Activation Functions (7.2) - Deep Learning & Neural Networks - Advance Machine Learning
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Activation Functions

Practice - Activation Functions

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary purpose of an activation function in a neural network?

💡 Hint: Think about why we can't use just linear functions.

Question 2 Easy

What output range does a sigmoid function produce?

💡 Hint: It's often used in binary classifications.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary output range of the Sigmoid function?

-1 to 1
0 to 1
0 to infinity

💡 Hint: Remember which context it is generally used in.

Question 2

True or False: The Tanh function is centered at zero, while Sigmoid is not.

True
False

💡 Hint: Think about the center point of each function.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Analyze and explain why deep neural networks prefer ReLU and its variants over traditional functions like Sigmoid and Tanh for hidden layers.

💡 Hint: Consider how activation functions impact gradient flow during backpropagation.

Challenge 2 Hard

Consider a multi-class classification problem with an output layer using Sigmoid instead of Softmax. Discuss the advantages and disadvantages.

💡 Hint: Reflect on the nature of class probabilities in multi-class scenarios.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.