Data Science Miscellaneous MCQ Questions and Answers | Data Science MCQs

A. To increase model complexity

B. To add more features to the dataset

C. To bring all features to a similar scale for better model performance

D. To remove irrelevant features

A. Feature scaling

B. One-hot encoding

C. Data normalization

D. Text vectorization

A. Application Programming Interface

B. Advanced Programming Integration

C. Algorithmic Programming Interface

D. Automated Program Integration

A. To visualize data

B. To summarize data

C. To build predictive models

D. To determine if there is a significant difference or effect

A. Descriptive statistics

B. Exploratory data analysis

C. Inferential statistics

D. Data preprocessing

A. Data transformation

B. Data cleaning

C. Data aggregation

D. Data transformation

A. Encode, Tokenize, Leverage

B. Estimate, Test, Label

C. Extract, Transform, Load

D. Explore, Train, Learn

A. To create visualizations

B. To build predictive models

C. To collect more data

D. To compare two versions of a webpage or product to determine which one performs better

A. To prevent overfitting by adding a penalty term to the loss function

B. To remove outliers from the data

C. To increase model complexity

D. To reduce dimensionality

A. Data normalization

B. Text vectorization

C. Feature scaling

D. One-hot encoding