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IBM Watson Data Scientist v1 Sample Questions (Q51-Q56):

NEW QUESTION # 51
Which hyperparameter is NOT commonly adjusted in a deep learning model?

A. Activation function
B. The color of the model's output
C. Learning rate
D. Number of layers

Answer: B

NEW QUESTION # 52
What is data leakage in the context of model training?

A. Loss of data during the splitting process
B. Leakage of sensitive information due to poor data handling practices
C. A situation where the test data is not available
D. When data from outside the training dataset is accidentally included in the training process

Answer: D

NEW QUESTION # 53
When deploying models in Watson Machine Learning, what is essential for ensuring the models perform as expected in production?

A. Using the highest number of resources for every model
B. Limiting access to the model to a few select users
C. Deployment without any security measures
D. Continuous monitoring and evaluation of model performance

Answer: D

NEW QUESTION # 54
Profiling and visualizing data using Watson tools primarily helps in:

A. Simplifying the data collection process without analyzing quality
B. Identifying patterns, outliers, and insights in the data
C. Creating aesthetically pleasing presentations without regard to data relevance
D. Increasing the quantity of data for analysis

Answer: B

NEW QUESTION # 55
Understanding how to use libraries in Python within a deployment environment is essential for:

A. Deploying models that are incompatible with the deployment environment
B. Increasing the complexity and maintenance cost of the deployed solution
C. Leveraging specific functionalities for data analysis, manipulation, and model building
D. Ensuring that all models are developed without any external libraries

Answer: C

NEW QUESTION # 56
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