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

What is the primary purpose of the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework in the context of data science projects?

Options :

A : To provide a structured approach to the entire data science life cycle

B : To optimize model performance and accuracy

C : To facilitate collaboration among team members

D : To automate data preprocessing and feature engineering

Answer: A

Question 3

What is the primary purpose of model evaluation in machine learning?

Options :

A : To make predictions on new, unseen data

B : To preprocess the input data before training the model

C : To select the best hyperparameters for the model

D : To assess the performance and generalization ability of a trained model on unseen data

Answer: D

Question 4

What does the term "event detection" refer to in the context of specialized applications in data science?

Options :

A : Preprocessing raw sensor data before analysis

B : Selecting the best hyperparameters for a neural network model

C : Evaluating the performance of a trained machine learning model

D : Identifying significant occurrences or anomalies in time-series data

Answer: D

Question 5

What technique is commonly used for imputing missing values in a dataset by replacing them with randomly selected values from the variable?

Options :

A : Regression imputation

B : Random imputation

C : Mean imputation

D : Mode imputation

Answer: B

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