Practice Topic Modeling (8.7.2) - Non-Parametric Bayesian Methods - Advance Machine Learning
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Topic Modeling

Practice - Topic Modeling

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the main purpose of topic modeling?

💡 Hint: Think about what insights can be gained from text data.

Question 2 Easy

What does HDP stand for?

💡 Hint: It's related to a type of Bayesian modeling.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary benefit of using HDP over LDA?

Fixed number of topics
Shared topic allocation across documents
Requires more labeled data

💡 Hint: Think about the adaptability of the models.

Question 2

True or False: Topic modeling can only be used with structured documents.

True
False

💡 Hint: Consider the types of data topic modeling is often applied to.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Considering a set of scientific articles, devise a methodology leveraging HDP to categorize them into topics. What steps would you take?

💡 Hint: Think about how you would tailor your approach based on the nature of the text.

Challenge 2 Hard

You have documents from diverse sources, how would you ensure the accuracy of topic distributions in HDP?

💡 Hint: Consider common metrics used in model evaluation.

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Reference links

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