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C1000-154 Valid Test Practice - C1000-154 Learning Engine

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IBM Watson Data Scientist v1 Sample Questions (Q14-Q19):

NEW QUESTION # 14
When determining upskill requirements for a team working on a solution, it is important to consider:

A. The budget allocation for the project
B. The preferred programming languages of the team
C. The existing skill level of the team and the skills required for the project
D. The geographical location of the team members

Answer: C

NEW QUESTION # 15
What is the key difference between batch processing and streaming in data processing?

A. Batch processing processes data in large blocks at a time, whereas streaming processes data in real- time as it arrives
B. Batch processing processes data in large blocks at a time, whereas streaming processes data in real- time as it arrives
C. Batch processing involves real-time data processing, whereas streaming does not process data
D. Streaming is suitable for large, historical datasets, whereas batch processing is for real-time data analysis

Answer: B

NEW QUESTION # 16
What is a critical consideration when selecting the right model class for a given problem?

A. The model's ability to produce results quickly, regardless of accuracy.
B. The availability of high-performance computing resources.
C. The nature of the problem (e.g., classification, regression) and the characteristics of the data.
D. The theoretical complexity of the model, with more complex models always being preferred.

Answer: C

NEW QUESTION # 17
An E-retailer uses several important data sources, including web logs which contain all of the information on how customers navigate the web site. There are non-informative entries in the web logs that need to be removed.
During which phase should these non-informative entries be removed in the CRISP-DM model?

A. Data Preparation
B. Data Understanding
C. Business Understanding
D. Modeling

Answer: A

NEW QUESTION # 18
In the context of building models, why is it important to select a tool based on algorithm requirements and expertise?

A. Selecting a tool that matches the team's expertise ensures more efficient model development and troubleshooting.
B. It is legally required to use only certain tools for specific types of data.
C. All machine learning tools are essentially the same, making the selection process trivial.
D. Tools with the most features should always be selected to ensure model complexity.

Answer: A

NEW QUESTION # 19
......

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