1. What is data wrangling?

The process of cleaning and unifying complex data sets
The method of storing data efficiently
A type of machine learning model
The creation of visualizations for data
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2. What is the purpose of exploratory data analysis (EDA)?

To create predictive models
To summarize the main characteristics of the data
To deploy machine learning models
To collect new data
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3. What is a common method for feature selection?

K-means clustering
Decision Trees
Recursive Feature Elimination
Linear Regression
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4. What is a confusion matrix used for?

To organize data in rows and columns
To evaluate the performance of a classification model
To confuse the user
To calculate the accuracy of regression models
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5. What is the difference between supervised and unsupervised learning?

Supervised learning does not require labeled data, while unsupervised learning does
Supervised learning uses labeled data, while unsupervised learning uses unlabeled data
There is no difference
Supervised learning is used for clustering, while unsupervised learning is used for classification
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