Data Science Intermediate
Intermediate
This test measures your ability to work with data cleaning, visualization, and machine learning basics, including libraries like Matplotlib, Seaborn, and Scikit-learn. To improve your skills, read the Towards Data Science Guides and watch this hands-on Intermediate Data Science Tutorial.
1
Which of the following is NOT a common data preprocessing technique?
2
What is the purpose of cross-validation in machine learning?
3
Which metric would you use to evaluate a classification model with imbalanced classes?
4
What is the purpose of regularization in machine learning?
5
Which of the following is NOT a dimensionality reduction technique?
6
What is the main advantage of using a random forest over a single decision tree?
7
What is the purpose of the 'elbow method' in clustering?
8
Which of the following is NOT a common feature selection method?
9
What is the purpose of a confusion matrix?
10
Which of the following is NOT a common ensemble method?
11
What is the purpose of the learning rate in gradient descent?
12
Which of the following is NOT a common text preprocessing step in NLP?
13
What is the purpose of the train-test split?
14
Which of the following is NOT a common evaluation metric for regression models?
15
What is the purpose of the 'dropout' layer in neural networks?