Practice Modeling (1.3) - Natural Language Processing (NLP) in Depth - Artificial Intelligence Advance
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Practice - Modeling

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does Naive Bayes assume about word independence?

💡 Hint: Think about the 'naive' part of Naive Bayes.

Question 2 Easy

True or False: Support Vector Machines can be used for regression.

💡 Hint: Consider the different types of SVM tasks.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main assumption of Naive Bayes?

Words are dependent on each other
Words are independent of each other
Naive Bayes cannot classify text

💡 Hint: Recall the definition of 'naive' in Naive Bayes.

Question 2

True or False: LSTM can process long sequences effectively.

True
False

💡 Hint: Consider how LSTM manages information over time.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a scenario where an email needs to be categorized into spam or not spam. Describe how you would use Naive Bayes for classification, including the relevant features.

💡 Hint: Focus on how word frequency influences classification.

Challenge 2 Hard

In implementing a chatbot, explain how you might use both SVM and BERT to enhance user experience. Include strengths and weaknesses of each model.

💡 Hint: Think about separating tasks based on strengths.

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