70-774.pdf - https\/www.dumpsbase.com\/70-774.html Real Microsoft 70-774 Dumps 1.You are performing exploratory analysis of files that are encoded in a

70-774.pdf - https/www.dumpsbase.com/70-774.html Real...

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Real Microsoft 70-774 Dumps 1.You are performing exploratory analysis of files that are encoded in acomplex proprietary format. The format requires disk intensive accessto several dependent files in HDFS.You need to build an Azure Machine Learning model by using acanopy clustering algorithm. You must ensure that changes toproprietary file formats can be maintained by using the least amount ofeffort.Which Machine Learning library should you use? A. MicrosoftMLB. scikit-learnC. SparkRD. MahoutAnswer: C 2.You need to integrate code and formatted text into an Azure MachineLearning experiment that enables interactive execution.What should you use? 3.You have the following three training datasets for a restaurant: * User Feature * Item feature * Ratings of items by users You must recommend restaurants to a particular user based only on the users features. You need to use a Matchbox Recommender to make recommendations. page 1 / 13
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How many input parameters should you specify? 4.Note: This question is part of a series of questions that present thesame Scenario. Each question I the series contains a unique solutionthat might meet the stated goals. Some question sets might have morethan one correct solution while others might not have correct solution.You need to remove rows that have an empty value in a specificcolumn. The solution must use a native module. Which module shouldyou use? 5.Note: This question is part of a series of questions that present thesame Scenario. Each question I the series contains a unique solutionthat might meet the stated goals. Some question sets might have morethan one correct solution while others might not have correct solution.You are working on an Azure Machine Learning Experiment.You have the dataset configured as shown in the following table: page 2 / 13
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You need to ensure that you can compare the performance of the models and add annotations to the results.
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