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DP-100 Exam Microsoft Designing and Implementing a Data Science Solution on Azure DP-100 dumps
Designing and Implementing a Data Science Solution on Azure Skills measured Define and prepare the development environment (15-20%) Select development environment assess the deployment environment constraints analyze and recommend tools that meet system requirements select the development environment Set up development environment create an Azure data science environment configure data science work environments Quantify the business problem define technical success metrics quantify risks DP-100 dumps PDF
Question no 1 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). Answer: A DP-100 dumps
Question no 2 You need to select an environment that will meet the business and data requirements.Which environment should you use? Azure HDInsight with Spark Mllib B. Azure Cognitive Services C. Azure Machine Learning Studio D. Microsoft Machine Learning Server Answer: D DP-100 dumps PDF
Question no 3 You need to implement a scaling strategy for the local penalty detection data.Which normalization type should you use? A. Streaming B. Weight C. Batch D. Cosine Answer: C DP-100 dumps
Question no 4 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. Answer: D Explanation: The linear discriminate analysis method works only on continuous variables, not categorical or ordinal variables. Linear discriminates analysis is similar to analysis of variance (ANOVA) in that it works by comparing the means of the variables. Scenario: Data scientists must build notebooks in a local environment using automatic feature engineering and model building in machine learning pipelines. Experiments for local crowd sentiment models must combine local penalty detection data. All shared features for local models are continuous variables. DP-100 dumps PDF
Question no 5 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. Answer: A DP-100 dumps
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