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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. 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.

2. Which statistical method reduces the number of attributes by lumping highly correlated attributes together?

A) Synthetic Minority Over-sampling Technique (SMOTE)
B) Principal Component Analysis (PCA)
C) Binning
D) Long Short Term Memory Network (LSTM)

3. Cloud Pak for Data's integration with Spark allows users to:

A) Leverage distributed computing for processing large datasets efficiently
B) Use Spark exclusively for data visualization purposes
C) Perform complex computations on small datasets only
D) Avoid using any form of data processing or analysis

4. 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

5. To add data assets from the catalog to a project in Cloud Pak for Data, which step is essential?

A) Browsing data assets based solely on their names
B) Assessing the compatibility of data formats
C) Selecting random data sets for variety
D) Maximizing the volume of data regardless of relevance

Solutions: