Machine Learning Quiz: 01

Mejbah Ahammad -
Machine Learning Knowledge Quiz with Timer and Enhanced Explanations

Machine Learning Knowledge Quiz

Test your Machine Learning knowledge by answering the following questions:

Time Remaining: 05:00

1. Which of the following is a supervised learning algorithm?

A) Linear Regression B) K-Means Clustering C) Principal Component Analysis D) Apriori Algorithm

2. What does overfitting in a machine learning model imply?

A) The model performs well on training data but poorly on new data B) The model performs well on new data but poorly on training data C) The model has high bias D) The model has low variance

3. Which of the following techniques is used to reduce the dimensionality of data?

A) Principal Component Analysis B) Decision Trees C) K-Nearest Neighbors D) Gradient Descent

4. What is the purpose of the activation function in a neural network?

A) Introduce non-linearity into the network B) Normalize the input data C) Update the weights during training D) Reduce overfitting

5. In which scenario would you use a convolutional neural network?

A) Image recognition tasks B) Predicting stock prices C) Analyzing sequential data D) Clustering customer data

6. What does the term "ensemble learning" refer to in machine learning?

A) Combining multiple models to improve performance B) Using deep learning models exclusively C) Selecting the best model based on validation data D) Training models on ensemble data sets

7. Which of the following is a common method to prevent overfitting?

A) Regularization B) Increasing model complexity C) Reducing training data D) Removing validation data

8. What is the "curse of dimensionality" in machine learning?

A) Problems caused by high-dimensional data B) Issues arising from too much training data C) Challenges in low-dimensional data visualization D) Overfitting due to small datasets

9. Which of the following is NOT a type of gradient descent optimization?

A) Stochastic Gradient Descent B) Batch Gradient Descent C) Mini-batch Gradient Descent D) Linear Gradient Descent

10. What does the ROC curve represent in classification problems?

A) Trade-off between true positive rate and false positive rate B) Relationship between precision and recall C) Model accuracy over different thresholds D) Error rate of the model