Artificial Intelligence & Machine Learning

Core Algorithmic Principles and Practices

This quiz examines conceptual and practical understanding of widely-used machine learning algorithms and their associated concepts.

#neural networks#optimization#feature engineering#model evaluation#supervised learning#regularization#unsupervised methods#bias variance#statistical learning

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Total Questions

Difficulty Level

medium

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0/0

Quiz Questions

Answer all questions below and test your knowledge.

1
Which of the following techniques is specifically designed to reduce overfitting in a decision tree model?
Question 1
2
The k-means clustering algorithm requires the user to specify which of the following before training?
Question 2
3
In a binary classification task, you observe that your model has high accuracy on the training set but significantly lower accuracy on a hold-out test set. Which of the following is the most likely primary cause?
Question 3
4
What is the primary purpose of the regularization term added to the loss function in algorithms like Ridge and Lasso regression?
Question 4
5
In a multi-class classification problem, which of the following evaluation metrics is specifically designed to handle class imbalance?
Question 5
6
Which of the following statements accurately describes the role of an activation function in a neural network neuron?
Question 6
7
Principal Component Analysis (PCA) is most appropriately used for which of the following tasks?
Question 7
8
In the context of ensemble learning, the Random Forest algorithm primarily mitigates the overfitting of individual decision trees through what mechanism?
Question 8
9
The process of one-hot encoding a categorical feature with 5 distinct categories will create how many new binary features?
Question 9

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Core Algorithmic Principles and Practices

Quiz Intelligence

Quiz Questions

Which of the following techniques is specifically designed to reduce overfitting in a decision tree model?

The k-means clustering algorithm requires the user to specify which of the following before training?

In a binary classification task, you observe that your model has high accuracy on the training set but significantly lower accuracy on a hold-out test set. Which of the following is the most likely primary cause?

What is the primary purpose of the regularization term added to the loss function in algorithms like Ridge and Lasso regression?

In a multi-class classification problem, which of the following evaluation metrics is specifically designed to handle class imbalance?

Which of the following statements accurately describes the role of an activation function in a neural network neuron?

Principal Component Analysis (PCA) is most appropriately used for which of the following tasks?

In the context of ensemble learning, the Random Forest algorithm primarily mitigates the overfitting of individual decision trees through what mechanism?

The process of one-hot encoding a categorical feature with 5 distinct categories will create how many new binary features?

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