Machine Learning Hero

Quiz Part 2: Data Preprocessing and Classical Machine Learning

Chapter 3: Data Preprocessing and Feature Engineering

1. What is the purpose of data cleaning in data preprocessing?
   • a) To improve model performance by transforming features
   • b) To identify and handle missing data, remove duplicates, and correct errors
   • c) To scale data to a consistent range
   • d) To reduce the dimensionality of the dataset
2. Which technique is typically used for handling missing data?
   • a) One-hot encoding
   • b) Data augmentation
   • c) Imputation
   • d) PCA
3. Feature engineering involves which of the following?
   • a) Creating new features from existing ones
   • b) Reducing noise from the data
   • c) Increasing the number of samples in the dataset
   • d) Both a and b
4. Why is it important ...