Welcome to your Uncovering the Top Machine Learning Quizzes 2024 (Part 4) This quiz has multiple choice questions and each has only one correct answer.
Total Questions : 24
To pass this quiz you need to score 80% or above.
Time Provided : 45 minutes
Today's Date : 11 March 2026
All the best!!
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1. What is the primary objective of unsupervised learning?
2. What does the parameter 'axis' in the dropna() method represent?
3. What is an application of supervised learning?
4. What is an example of a real-world application of reinforcement learning?
5. What method in scikit-learn is commonly used for outlier detection based on the interquartile range?
6. Which function is commonly used to measure the difference between the predicted values of a model and the actual values in supervised learning?
7. How does cross-validation help in hyperparameter tuning?
8. What method can be used to handle missing data by replacing missing values with the mean of the column?
9. What is grid search in the context of hyperparameter tuning?
10. In which type of machine learning does the model learn from labeled data to make predictions or decisions?
11. In pandas, which method is used to drop rows with missing values from a DataFrame?
12. What term refers to the parameters in a machine learning model that are adjusted during the training process to minimize a specified cost function?
13. Which technique involves removing data points that fall outside a specified range of values?
14. Which machine learning method is used when there are no labeled responses?
15. What is feature extraction in feature engineering?
16. Which machine learning method is commonly used in natural language processing (NLP) tasks such as sentiment analysis?
17. What is the purpose of hyperparameter tuning in machine learning?
18. In which of the following ML methods, the model learns by interacting with an environment and receiving feedback in the form of rewards or penalties?
19. Which Python library offers the 'SimpleImputer' class for handling missing data?
20. Which of the following is an example of supervised learning algorithm?
21. What is a technique used for feature scaling that transforms the data to have zero mean and unit variance?
22. What is a technique used for feature scaling that transforms the data into a range between 0 and 1?
23. Which algorithm can be used for clustering in unsupervised learning?
24. In Python, which function is used for Z-score normalization?
