Practice Construct And Train A Baseline Multi-layer Perceptron (mlp) (lab.2) - Introduction to Deep Learning (Weeks 11)
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Construct and Train a Baseline Multi-Layer Perceptron (MLP)

Practice - Construct and Train a Baseline Multi-Layer Perceptron (MLP)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does MLP stand for?

💡 Hint: Think about the layers in a neural network.

Question 2 Easy

Name one common activation function used in MLPs.

💡 Hint: It's usually applied in hidden layers.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the role of an activation function in an MLP?

To introduce non-linearity
To calculate loss
To optimize weights

💡 Hint: Think of it as a switch that decides whether a neuron 'fires'.

Question 2

True or False: The number of epochs determines how many times the training data is processed in MLP training.

True
False

💡 Hint: Consider the definition of an epoch.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Build a comprehensive MLP model from scratch using Keras for a tabular dataset. Document each stage from data preparation to evaluation.

💡 Hint: Consider if you'll need to adjust for unbalanced classes in the dataset.

Challenge 2 Hard

Compare and contrast the performance of two different activation functions in an MLP trained on a specific dataset.

💡 Hint: What differences do you expect in convergence rates between these functions?

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Reference links

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