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Skills Measured :
This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area in the exam. The higher the percentage, the more questions you are likely to see on that content area in the exam. View video tutorials about the variety of question types on Microsoft exams.
Technology: Microsoft Azure
You need to implement a new cost factor scenario for the ad response models as illustrated in the
performance curve exhibit.Which technique should you use?
A. Set the threshold to 0.5 and retrain if weighted Kappa deviates +/- 5% from 0.45.
B. Set the threshold to 0.05 and retrain if weighted Kappa deviates +/- 5% from 0.5.
C. Set the threshold to 0.2 and retrain if weighted Kappa deviates +/- 5% from 0.6.
D. Set the threshold to 0.75 and retrain if weighted Kappa deviates +/- 5% from 0.15.
You need to implement a model development strategy to determine a user’s tendency to respond to and.Which technique should you use?
A. Use a Relative Expression Split module to partition the data based on centroid distance.
B. Use a Relative Expression Split module to partition the data based on distance travelled to the event.
C. Use a Split Rows module to partition the data based on distance travelled to the event.
D. Use a Split Rows module to partition the data based on centroid distance.
You need to implement a feature engineering strategy for the crowd sentiment local models.What should you do?
A. Apply an analysis of variance (ANOVA).
B. Apply a Pearson correlation coefficient.
C. Apply a Spearman correlation coefficient.
D. Apply a linear discriminant analysis.
You need to implement a scaling strategy for the local penalty detection data.Which normalization type should you use?
You need to select an environment that will meet the business and data requirements.Which environment should you use?
A. Azure HDInsight with Spark MLlib
B. Azure Cognitive Services
C. Azure Machine Learning Studio
D. Microsoft Machine Learning Server
You need to resolve the local machine learning pipeline performance issue. What should you do?
A. Increase Graphic Processing Units (GPUs).
B. Increase the learning rate.
C. Increase the training iterations,
D. Increase Central Processing Units (CPUs).