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NEW QUESTION # 18
When building a deep learning neural network, what is the purpose of the activation function in each neuron?
- A. To initialize the model
- B. To introduce non-linearity
- C. To define the learning rate
- D. To control the number of hidden layers
Answer: B
NEW QUESTION # 19
Which data source typically provides access to real-time financial market data?
- A. Online news websites
- B. Stock market APIs
- C. Social media platforms
- D. Weather stations
Answer: B
NEW QUESTION # 20
Which of the following metrics is commonly used to evaluate the performance of a binary classification model in a machine learning pipeline?
- A. Root Mean Squared Error (RMSE)
- B. Accuracy
- C. Mean Absolute Error (MAE)
- D. R-squared
Answer: B
NEW QUESTION # 21
What is the main advantage of using a RESTful API (Representational State Transfer) as a data source?
- A. Support for complex data structures
- B. Simple and standardized communication
- C. Real-time data processing
- D. High security features
Answer: B
NEW QUESTION # 22
What is the main advantage of ensemble methods in model building?
- A. They combine multiple models to improve predictive performance
- B. They produce simple and interpretable models
- C. They work well with high-dimensional data
- D. They require minimal data preprocessing
Answer: A
NEW QUESTION # 23
What does "data lineage" refer to in the context of data source management?
- A. The physical location of data storage
- B. The history of data transformation processes
- C. The structure of a relational database
- D. The security protocols for data access
Answer: B
NEW QUESTION # 24
Which of the following is a common technique for handling missing data in a machine learning pipeline?
- A. Deleting rows with missing data
- B. Ignoring missing data
- C. Imputing missing values
- D. Replacing missing values with zeros
Answer: C
NEW QUESTION # 25
Which type of data source typically stores structured data in a tabular format?
- A. Relational databases
- B. APIs
- C. Text documents
- D. NoSQL databases
Answer: A
NEW QUESTION # 26
What is a data lake architecture designed to store primarily?
- A. Highly structured data in tabular format
- B. All types of data, including structured and unstructured data
- C. Data from a single source or department
- D. Only unstructured data in raw form
Answer: B
NEW QUESTION # 27
What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?
- A. To prevent overfitting and reduce model complexity
- B. To add more features to the model
- C. To increase model complexity
- D. To speed up model training
Answer: A
NEW QUESTION # 28
What is the primary purpose of model documentation in the model deployment phase?
- A. To create synthetic data
- B. To evaluate the model's accuracy
- C. To assess data quality
- D. To provide information on the model's development, architecture, and usage
Answer: D
NEW QUESTION # 29
What is metadata in the context of data sources?
- A. Data that is encrypted for security
- B. Data that is in a non-standard, proprietary format
- C. Data about data, providing information such as data source, structure, and context
- D. Data that is stored in a physical format
Answer: C
NEW QUESTION # 30
What is the main purpose of feature engineering in model building?
- A. Creating new features or transforming existing ones to improve model performance
- B. Data visualization
- C. Model evaluation
- D. Data preprocessing
Answer: A
NEW QUESTION # 31
What does the term "bias" in machine learning refer to?
- A. Systematic errors that cause a model to consistently underpredict or overpredict
- B. A model's inability to generalize to new data
- C. The simplicity of a model
- D. The overall accuracy of a model
Answer: A
NEW QUESTION # 32
In a supervised machine learning pipeline, what is the purpose of the test data set?
- A. To evaluate the model's predictions
- B. To train the machine learning model
- C. To validate the model's performance
- D. To preprocess the data
Answer: C
NEW QUESTION # 33
In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?
- A. To visualize data distribution
- B. To evaluate the mean squared error of a model
- C. To compare models' performance in terms of sensitivity and specificity
- D. To measure feature importance
Answer: C
NEW QUESTION # 34
What is the primary purpose of model assessment in the context of data science and machine learning?
- A. Data visualization
- B. Evaluating and selecting the best-performing model
- C. Model building
- D. Data preprocessing
Answer: B
NEW QUESTION # 35
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