{"description":"Test your knowledge of normalization, standardization, and why data scaling is crucial for machine learning.","questions":[{"answer":"To ensure consistent feature influence and avoid bias","number":1,"options":["To increase model complexity","To ensure consistent feature influence and avoid bias","To convert data into binary format","To eliminate all outliers"],"question":"What is the primary purpose of data scaling in machine learning?"},{"answer":"Normalization and standardization","number":2,"options":["One-hot encoding and PCA","Normalization and standardization","Regression and classification","Bagging and boosting"],"question":"Which of the following are two common methods of data scaling?"},{"answer":"Min-max scaling","number":3,"options":["Z-score transformation","Min-max scaling","Feature hashing","Variance reduction"],"question":"Normalization is also referred to as:"},{"answer":"[-1, 1] or [0, 1]","number":4,"options":["[-100, 100]","[-1, 1] or [0, 1]","[mean \u00b1 std]","Any range that includes outliers"],"question":"Which value range is typically used in normalization?"},{"answer":"A mean of 0 and standard deviation of 1","number":5,"options":["Values between 0 and 1","A mean of 1 and std of 10","A mean of 0 and standard deviation of 1","Discrete integer categories"],"question":"Standardization transforms data to have:"},{"answer":"It improves gradient convergence and learning speed","number":6,"options":["It helps models overfit less","It improves gradient convergence and learning speed","It reduces memory usage","It changes labels into numbers"],"question":"Why is data scaling important for optimization algorithms in neural networks?"},{"answer":"When features are skewed and need to fit a fixed scale","number":7,"options":["When the data follows a normal distribution","When features are skewed and need to fit a fixed scale","When data is already centered","When outliers must be retained"],"question":"When should normalization be preferred over standardization?"},{"answer":"It may lead to biased predictions due to dominant features","number":8,"options":["It improves model generalization","It has no effect if the dataset is large","It may lead to biased predictions due to dominant features","It always increases accuracy"],"question":"What effect does unscaled data have on machine learning models?"}],"title":"Data Scaling"}