[Jan 05, 2025] New A00-406 Exam Dumps with High Passing Rate
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NEW QUESTION # 40
Which technique is commonly used for feature scaling or normalization in machine learning pipelines?
- A. Decision Trees
- B. Principal Component Analysis (PCA)
- C. One-Hot Encoding
- D. Standardization
Answer: D
NEW QUESTION # 41
What is the primary purpose of model deployment in the context of data science and machine learning?
- A. Model evaluation
- B. Making the model available for use in real-world applications
- C. Data preprocessing
- D. Model building
Answer: B
NEW QUESTION # 42
Which algorithm is commonly used for decision-making tasks in classification models?
- A. Linear Regression
- B. Decision Trees
- C. Principal Component Analysis (PCA)
- D. K-Means
Answer: B
NEW QUESTION # 43
When deploying a machine learning model, what is "model drift"?
- A. The process of feature extraction
- B. A sudden increase in the model's accuracy
- C. A change in the distribution of the input data or target variable over time
- D. A measure of feature importance
Answer: C
NEW QUESTION # 44
In natural language processing, what does "stemming" involve?
- A. Reducing words to their base or root form
- B. Creating new words to improve model performance
- C. Converting text to numbers for model input
- D. Grouping similar words together based on their meanings
Answer: A
NEW QUESTION # 45
What is "model deployment" in the context of data science and machine learning?
- A. Making the model available for use in real-world applications
- B. The process of selecting features
- C. The process of data cleaning
- D. The process of building a model
Answer: A
NEW QUESTION # 46
Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?
- A. Naive Bayes
- B. Regularization
- C. Principal Component Analysis (PCA)
- D. One-Hot Encoding
Answer: B
NEW QUESTION # 47
What is the primary goal of hyperparameter tuning during model building?
- A. To optimize the settings that control the model's learning process
- B. To add more features to the model
- C. To increase model complexity
- D. To improve data preprocessing techniques
Answer: A
NEW QUESTION # 48
What does "data lineage" refer to in the context of data source management?
- A. The physical location of data storage
- B. The security protocols for data access
- C. The structure of a relational database
- D. The history of data transformation processes
Answer: D
NEW QUESTION # 49
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 is too simple and underperforms.
- C. Overfitting is not a concern in machine learning pipelines.
- D. Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.
Answer: D
NEW QUESTION # 50
Which of the following is a common source for external data in the context of business analytics?
- A. Company financial reports
- B. CRM data
- C. Intranet databases
- D. Employee records
Answer: A
NEW QUESTION # 51
What is "model versioning" in the context of model deployment?
- A. The process of training a model from scratch
- B. The process of evaluating model performance
- C. The practice of keeping track of different versions of a model to maintain reproducibility
- D. The process of creating synthetic data
Answer: C
NEW QUESTION # 52
Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?
- A. MySQL
- B. Oracle Database
- C. MongoDB
- D. Microsoft SQL Server
Answer: C
NEW QUESTION # 53
In model assessment, what does "cross-validation" aim to address?
- A. Model deployment
- B. Data preprocessing
- C. Overfitting and generalization
- D. Training a model
Answer: C
NEW QUESTION # 54
What is the main purpose of feature engineering in model building?
- A. Data visualization
- B. Model evaluation
- C. Creating new features or transforming existing ones to improve model performance
- D. Data preprocessing
Answer: C
NEW QUESTION # 55
Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?
- A. Learning rate
- B. Max features
- C. Min samples split
- D. Max depth
Answer: D
NEW QUESTION # 56
What is the purpose of a confusion matrix in the context of classification models?
- A. To visualize the data
- B. To compute the mean squared error
- C. To evaluate model performance, especially for binary classification
- D. To summarize the distribution of target variables
Answer: C
NEW QUESTION # 57
Which evaluation metric is commonly used for assessing the performance of a binary classification model?
- A. Accuracy
- B. Mean Absolute Error (MAE)
- C. Root Mean Squared Error (RMSE)
- D. R-squared
Answer: A
NEW QUESTION # 58
In reinforcement learning, what is the "reward signal"?
- A. The final prediction made by the model
- B. A regularization parameter
- C. The accuracy of the model's predictions
- D. A numerical value that indicates the performance of an action taken by the agent
Answer: D
NEW QUESTION # 59
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