Practice Generative Models With Latent Variables (5.2) - Latent Variable & Mixture Models
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Generative Models with Latent Variables

Practice - Generative Models with Latent Variables

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define a latent variable in your own words.

💡 Hint: Think about examples in psychology or recommendations.

Question 2 Easy

What is the equation that represents the relationship between latent and observed variables?

💡 Hint: Remember the format of a joint probability distribution.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a generative model?

A model that predicts unobservable variables.
A model that defines data generation through latent variables.
A model that strictly uses observed variables.

💡 Hint: Think about the role of hidden factors in observable data.

Question 2

True or False: Marginal likelihood requires integration or summation over latent variables.

True
False

💡 Hint: Recall the definitions given earlier in our discussion.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a dataset where you suspect hidden factors influence customer purchases in a store. How would you approach building a generative model to discover these factors?

💡 Hint: Think about what data you have and how latent variabilities may explain observable actions.

Challenge 2 Hard

Derive the marginal likelihood for a continuous variable in terms of latent variables. Explain the significance of each component in your equation.

💡 Hint: Remember, understanding how different latent distributions interact with your observed data is essential.

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Reference links

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