Machine Learning Intermediate
IntermediateThis test measures your ability to build and train machine learning models using Python, Scikit-learn, and TensorFlow, along with concepts like feature engineering and evaluation metrics. To improve your skills, check the Scikit-learn User Guide and watch this practical Intermediate Machine Learning Tutorial.
1
What is the purpose of the validation set in machine learning?
2
What is the main advantage of using Random Forest over a single Decision Tree?
3
What is the purpose of the learning rate in gradient descent?
4
Which of the following is NOT a common ensemble method?
5
What is the purpose of regularization in machine learning?
6
What is the main advantage of using cross-validation?
7
Which of the following is NOT a common approach to handle imbalanced datasets?
8
What is the purpose of the activation function in a neural network?
9
Which of the following is NOT a common optimization algorithm for training neural networks?
10
What is the purpose of dropout in neural networks?
11
Which of the following is NOT a common evaluation metric for classification problems?
12
What is the purpose of early stopping in neural networks?
13
Which of the following is NOT a common approach to handle categorical variables?
14
What is the purpose of batch normalization in neural networks?
15
Which of the following is NOT a common type of neural network architecture?
16
What is the purpose of the learning rate scheduler in deep learning?