70-774 Exam
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Q21. 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.
How many input parameters should you specify?
A. 1
B. 2
C. 3
D. 4
Answer: D
Q22. You have data about the following:
* Users
* Movies
* User ratings of the movies
You need to predict whether a user will like a particular movie. Which Matchbox recommender should you use?
A. Item Recommendation
B. Related items
C. Rating Prediction
D. Related Users.
Answer: B
Q23. Note: This question is part of a series of questions that present the same Scenario. Each question I the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution while others might not have correct solution.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs. You plan to detect the presence of trees in the photographs.
* Hidden Layers that support a directed graph structure.
* User-defined core components on the GPU
Solution: You create a Machine Learning Experiment that implements the Multiclass Neural Network Module.
Does this meet the goal?
A. YES
B. NO
Answer: A
Q24. You are building an Azure Machine Learning Solution for an Online retailer.
When a customer selects a product, you need to recommend products that the customer might like to purchase at the same time. The recommendation should be based on what other customers purchased the same product.
Which model should you use?
A. Collaborative Filtering
B. Boosted Decision Tree Regression Model
C. Two-Class boosted decision tree
D. K-Means Clustering
Answer: A
Q25. Note: This question is part of a series of questions that present the same Scenario. Each question I the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution while others might not have correct solution.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs. You plan to detect the presence of trees in the photographs.
* Hidden Layers that support a directed graph structure.
* User-defined core components on the GPU
Solution: You create a Machine Learning Experiment that implements the Multiclass Neural Network Module.
Does this meet the goal?
A. YES
B. NO
Answer: A
Q26. You are analyzing taxi trips in New York City. You leverage the Azure Data Factory to create data pipelines and to orchestrate data movement.
You plan to develop a predictive model for 170 million rows (37 GB) of raw data in Apache Hive by using Microsoft R Serve to identify which factors contributes to the passenger tipping behavior.
All of the platforms that are used for the analysis are the same. Each worker node has eight processor cores and 28 GB Of memory.
Which type of Azure HDInsight cluster should you use to produce results as quickly as possible?
A. Hadoop
B. HBase
C. Interactive Hive
D. Spark
Answer: A
Q27. Note: This question is part of a series of questions that present the same Scenario. Each question I the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution while others might not have correct solution.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs. You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
* Hidden Layers that support a directed graph structure.
* User-defined core components on the GPU
Solution: You create a Machine Learning Experiment that implements the Multiclass Decision Jungle Module.
Does this meet the goal?
A. YES
B. NO
Answer: B