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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. Which analytic technique is NOT typically used to address business requirements?

A) Regression analysis
B) Decision trees
C) Proofreading
D) Clustering

2. Given the Confusion matrix below, which is the formula for specificity?

A) TN/(TN + FP)
B) (TP + TN)/(FN + FP + TN + TP)
C) TP/(FP + TP)
D) TP/(FN + TP)

3. How do you determine which tool to use based on algorithm requirements and expertise?

A) Select tools that the team is already familiar with, even if they are not the best fit for the algorithm.
B) Always use the most complex tool to ensure the model's accuracy.
C) Consider the tool's compatibility with the algorithm requirements and the team's expertise.
D) Choose the newest tools on the market for the most up-to-date features.

4. In unsupervised learning, which algorithm is best suited for grouping customers based on their purchase history to target marketing efforts more effectively?

A) Linear Regression
B) Support Vector Machines
C) K-Means Clustering
D) Decision Trees

5. 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.

Solutions: