Practice Perceptrons To Multi-layer Perceptrons (mlps) (11.2) - Introduction to Deep Learning (Weeks 11)
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Perceptrons to Multi-Layer Perceptrons (MLPs)

Practice - Perceptrons to Multi-Layer Perceptrons (MLPs)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a Perceptron?

💡 Hint: Think about how it classifies data.

Question 2 Easy

What layers are present in an MLP?

💡 Hint: Count the types of layers involved.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main function of a Perceptron?

To classify data
To compute averages
To store data

💡 Hint: Think about its role in AI and machine learning.

Question 2

True or False: Multi-Layer Perceptrons can only classify linearly separable data.

True
False

💡 Hint: Consider how MLPs differ from single-layer Perceptrons.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset that you believe is non-linearly separable, outline how you would design an MLP to classify the data.

💡 Hint: Consider the complexity of the data and how many layers might be necessary.

Challenge 2 Hard

Explain why activation functions are critical for MLPs and provide examples of different types.

💡 Hint: Think about the linear vs. non-linear capabilities.

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Reference links

Supplementary resources to enhance your learning experience.