Practice Construct and Train a Baseline Multi-Layer Perceptron (MLP) - lab.2 | Module 6: Introduction to Deep Learning (Weeks 11) | Machine Learning
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lab.2 - Construct and Train a Baseline Multi-Layer Perceptron (MLP)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does MLP stand for?

πŸ’‘ Hint: Think about the layers in a neural network.

Question 2

Easy

Name one common activation function used in MLPs.

πŸ’‘ Hint: It's usually applied in hidden layers.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

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

  • To introduce non-linearity
  • To calculate loss
  • To optimize weights

πŸ’‘ 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

πŸ’‘ Hint: Consider the definition of an epoch.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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

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

Question 2

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

πŸ’‘ Hint: What differences do you expect in convergence rates between these functions?

Challenge and get performance evaluation