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IBM Watson Data Scientist v1 Sample Questions:

1. Which statement best differentiates machine learning from deep learning?

A) Machine learning algorithms perform better on structured data, while deep learning excels with unstructured data like images and text.
B) Deep learning algorithms require less data to learn.
C) Machine learning models are always transparent, whereas deep learning models cannot be interpreted.
D) Deep learning algorithms are a subset of machine learning algorithms that do not require feature engineering.

2. Which hyperparameter is NOT commonly adjusted in a deep learning model?

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

3. Automating data processing and model deployment with jobs in Watson Studio helps to:

A) Limit the ability to update models based on new data
B) Enhance the reproducibility and efficiency of model deployments
C) Increase the need for manual intervention in the model lifecycle
D) Reduce the scalability of deployed solutions

4. Which two packages can be used to customize the software configuration of a Jupyter notebook environment in Cloud Pak for Data?

A) conda
B) sudo
C) vim
D) pip
E) bash

5. Understanding how to use libraries in Python within a deployment environment is essential for:

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

Solutions: