Question 1

What method of supervised machine learning is used for predicting continuous numeric outcomes?

Options :

A : Classifiers

B : Regressors

C : Embeddings

D : Recommender systems

Answer: B

Question 2

A data scientist has built an image recognition model that distinguishes cars from trucks. The data scientist now wants to measure the rate at which the model correctly identifies a car as a car versus when it misidentifies a truck as a car. Which of the following would best convey this information?

Options :

A : Confusion matrix

B : AUC/ROC curve

C : Box plot

D : Correlation plot

Answer: A

Question 3

What does the acronym "ALS" stand for in the context of recommender systems?

Options :

A : Alternating Least Squares

B : Aggregated Least Squares

C : Average Least Squares

D : Adaptive Learning System

Answer: A

Question 4

Which statistical metric measures the proportion of variance explained by a regression model?

Options :

A : R-squared

B : F statistic

C : Adjusted R-squared

D : Root mean square error (RMSE)

Answer: A

Question 5

What is the primary goal of regularization techniques in machine learning?

Options :

A : To reduce overfitting

B : To increase variance

C : To reduce bias

D : To increase model complexity

Answer: A

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