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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

Question 1

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

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

Question 2

F1-score is particularly useful when:

A. The data is completely balanced.
B. The dataset size is extremely large.
C. Only the model's accuracy matters.
D. You need a balance between precision and recall.

Question 3

A model's performance is not solely dependent on its accuracy but also on:

A. Metrics like precision, recall, and F1 score
B. The choice of programming language
C. The number of features selected
D. The color of the visualization charts

Question 4

In the context of assessing data quality in Watson Knowledge Catalog (WKC) and Cloud Pak for Data (CPD), what is a primary focus?

A. Increasing the volume of data collected
B. Focusing on the data's color scheme
C. Analyzing completeness, consistency, and accuracy of data
D. Enhancing the graphical user interface

Question 5

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

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

Solutions: