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Question 1

In machine learning, what term describes the process of selecting the best set of hyperparameters for a model?

Options :

A : Model deployment

B : Model validation

C : Feature engineering

D : Hyperparameter tuning

Answer: D

Question 2

What does the term "heuristics" refer to in the context of data science?

Options :

A : Metrics used to evaluate the performance of a trained model

B : Preprocessing steps applied to the input data before training the model

C : Techniques for optimizing the performance of machine learning models

D : Problem-solving techniques or strategies that prioritize speed and efficiency over accuracy

Answer: D

Question 3

A data analyst wants to find the latitude and longitude of a mailing address. Which of the following is the best method to use?

Options :

A : One-hot encoding

B : Binning

C : Geocoding

D : Imputing

Answer: C

Question 4

What is the primary purpose of Monte Carlo simulation in probability and statistics?

Options :

A : To estimate the probability of different outcomes by running simulations

B : To calculate confidence intervals

C : To perform hypothesis tests

D : To generate random samples from a probability distribution

Answer: A

Question 5

What is the primary purpose of reinforcement learning in machine learning?

Options :

A : To enable agents to learn optimal actions through trial and error

B : To preprocess the input data before training the model

C : To select the best hyperparameters for the model

D : To evaluate the performance of a trained model

Answer: A