[2024] A00-406 Answers A00-406 Free Demo Are Based On The Real Exam
A00-406 [Oct-2024 Newly Released] Exam Questions For You To Pass
NEW QUESTION # 30
What is the primary objective of model evaluation in the context of building predictive models?
- A. Discovering patterns in data
- B. Visualizing data
- C. Assessing the model's performance and accuracy
- D. Cleaning the data
Answer: C
NEW QUESTION # 31
What is a data lake architecture designed to store primarily?
- A. Data from a single source or department
- B. Only unstructured data in raw form
- C. All types of data, including structured and unstructured data
- D. Highly structured data in tabular format
Answer: C
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 preprocess the data
- D. To validate the model's performance
Answer: D
NEW QUESTION # 33
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. Replacing missing values with zeros
- D. Imputing missing values
Answer: D
NEW QUESTION # 34
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 require minimal data preprocessing
- D. They work well with high-dimensional data
Answer: A
NEW QUESTION # 35
In reinforcement learning, what is the "reward signal"?
- A. The accuracy of the model's predictions
- B. The final prediction made by the model
- C. A regularization parameter
- D. A numerical value that indicates the performance of an action taken by the agent
Answer: D
NEW QUESTION # 36
Which type of model is typically used for time-series forecasting?
- A. K-Means Clustering
- B. AutoRegressive Integrated Moving Average (ARIMA)
- C. Logistic Regression
- D. Decision Trees
Answer: B
NEW QUESTION # 37
What is overfitting in machine learning, and how can it be addressed in a pipeline?
- A. Overfitting occurs when the model is too complex and overperforms.
- B. Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.
- C. Overfitting occurs when the model is too simple and underperforms.
- D. Overfitting is not a concern in machine learning pipelines.
Answer: B
NEW QUESTION # 38
Which algorithm is commonly used for decision-making tasks in classification models?
- A. Decision Trees
- B. Principal Component Analysis (PCA)
- C. Linear Regression
- D. K-Means
Answer: A
NEW QUESTION # 39
Which type of model is well-suited for solving classification problems when dealing with high- dimensional data, such as text?
- A. K-Means Clustering
- B. Linear Regression
- C. Support Vector Machine (SVM)
- D. Random Forest
Answer: C
NEW QUESTION # 40
Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?
- A. Principal Component Analysis (PCA)
- B. K-Means Clustering
- C. Linear Regression
- D. Support Vector Machine (SVM)
Answer: D
NEW QUESTION # 41
In reinforcement learning, what is the agent's objective?
- A. To generate synthetic data
- B. To make predictions
- C. To learn from labeled data
- D. To maximize a cumulative reward over time
Answer: D
NEW QUESTION # 42
What is the purpose of an ROC curve (Receiver Operating Characteristic) in model assessment?
- A. To evaluate regression models
- B. To compare a model's true positive rate with the false positive rate
- C. To measure feature importance
- D. To visualize data distribution
Answer: B
NEW QUESTION # 43
In the context of model building, what is the purpose of hyperparameter tuning?
- A. Training the model
- B. Visualizing data
- C. Selecting the most important features
- D. Optimizing the model's hyperparameters for better performance
Answer: D
NEW QUESTION # 44
What is the primary function of a data catalog in managing data sources?
- A. Data analysis
- B. Data documentation and discovery
- C. Data storage
- D. Data visualization
Answer: B
NEW QUESTION # 45
Which evaluation metric is commonly used for assessing the performance of a regression model?
- A. Precision
- B. Mean Absolute Error (MAE)
- C. Confusion Matrix
- D. F1 Score
Answer: B
NEW QUESTION # 46
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