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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. In defining a business problem, what is essential to align with the stakeholders?

A) Business objectives
B) Data sources
C) Technical requirements
D) Project milestones

3. Selecting the right model for a data science project depends on:

A) The size of the dataset only
B) The project's budget only
C) The type of data and the problem to be solved
D) The preference of the data scientist

4. Which of the following is NOT a type of data source commonly integrated with Cloud Pak for Data?

A) Cloud storage services
B) Paper-based records
C) Social media feeds
D) Proprietary in-memory databases

5. What is the primary purpose of hyperparameter tuning in machine learning models?

A) To ensure the model uses all available computational resources
B) To adjust the model's complexity to improve its performance on unseen data
C) To increase the number of features in the dataset automatically
D) To reduce the training time of the model to an absolute minimum

Solutions: