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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does 'statistical methods' refer to in NLP?
💡 Hint: Think about how numbers help in understanding text.
Question 2
Easy
Give an example of a statistical method in NLP.
💡 Hint: Consider a method used in spam detection.
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
Statistical methods in NLP primarily rely on:
- A. Manual coding
- B. Large datasets
- C. Hardcoded rules
💡 Hint: Think about what statistical analysis requires.
Question 2
True or False: Naive Bayes assumes independence between features.
- True
- False
💡 Hint: Consider the assumptions behind statistical classifiers.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Analyze a dataset of emails and implement a Naive Bayes classifier to classify them into spam and non-spam. Discuss the performance and challenges encountered.
💡 Hint: Focus on feature selection and thresholds.
Question 2
Compare the effectiveness of Naive Bayes against another method like Logistic Regression on a specific NLP task.
💡 Hint: Consider advantages in computational efficiency and simplicity.
Challenge and get performance evaluation