Practice Free D-DS-FN-23 Exam Online Questions
In which lifecycle stage are appropriate analytical techniques determined?
- A . Model planning
- B . Model building
- C . Data preparation
- D . Discovery
What metrics are used to help calculate relevance in text analysis?
- A . TF and R square
- B . IDF and information gain
- C . Information gain and confidence interval
- D . TF and IDF
In a fitted ARIMA(1,2,3) model, how many differences are applied?
- A . 0
- B . 1
- C . 2
- D . 3
In a fitted ARIMA(1,2,3) model, how many differences are applied?
- A . 0
- B . 1
- C . 2
- D . 3
If distributed Item-based Collaborative Filtering is an algorithm supported by Mahout, what is the use case category of the algorithm?
- A . Classification
- B . Recommenders
- C . Frequent Itemset
- D . Clustering
Which ROC curve represents a perfect model fit?
A)
B)
C)
D)
- A . Exhibit A
- B . Exhibit B
- C . Exhibit C
- D . Exhibit D
Executives want to determine whether a change in a shopping rewards program has been effective in getting customers to increase their spending.
Which approach could be used to determine if a significant shift in spending has occurred?
- A . Hypothesis testing
- B . Sample variance
- C . K-means clustering
- D . Naive
A disk drive manufacturer has a defect rate of less than 1.0% with 98% confidence. A quality assurance team samples 1000 disk drives and finds 14 defective units.
Which action should the team recommend?
- A . The manufacturing process should be inspected for problems.
- B . A larger sample size should be taken to determine if the plant is functioning properly
- C . A smaller sample size should be taken to determine if the plant is functioning properly
- D . The manufacturing process is functioning properly and no further action is required.
In which lifecycle stage are initial hypotheses formed?
- A . Discovery
- B . Model planning
- C . Model building
- D . Data preparation
After which phase of the data analytics lifecycle should you determine if the model is robust enough?
- A . Discovery
- B . Operationalize
- C . Data preparation
- D . Model building