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Practice Questions
Test your understanding with targeted questions related to the topic.
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.
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 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.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
Question 2
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.
Challenge and get performance evaluation