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You need to remove rows that have an empty value in a specific column. The solution must use a native module. Which module should you use?
Execute Python Script
Tune Model Hyperparameters
Select Columns in Dataset
Clean Missing Data
You are building an Azure Machine Learning Experiment. You need to transform 47 numeric columns into a set of 10 linearly uncorrelated features. Which module should you add to the experiment?
Principal Component Analysis
Group Data into Bins
You need to use only one percent of an Apache hive Data table by conducting random sampling by groups. Which module should you use?
Tune Model Hyperparameters.
Clean Missing Data
Select Columns in Dataset
Execute Python Script
You plan to use Azure Machine Learning to develop a predictive model. You plan to include an Execute Python Script module. What capability does the module provide?
outputting a file to a network location
performing interactive debugging of a Python script
saving the result of a Python script run in a Machine Learning environment to a local file
visualizing univariate and multivariate summaries by using Python code
A Travel agency named Margie’s Travel sells airline tickets to customers in the United States. Margie’s Travel wants you to provide insights and predictions on flight delays. The agency is considering implementing a system that will communicate to its customers as the flight departure near about possible delays due to weather conditions. The flight data contains the following attributes:
DepartureDate: The departure date aggregated at a per hour granularity.
Carrier: The code assigned by the IATA and commonly used to identify a carrier.
OriginAirportID: An identification number assigned by the USDOT to identify a unique airport (the flight’s Origin)
DestAirportID: The departure delay in minutes.
DepDet30: A Boolean value indicating whether the departure was delayed by 30 minutes or more ( a value of 1 indicates that the departure was delayed by 30 minutes or more)
The weather data contains the following Attributes: AirportID, ReadingDate (YYYY/MM/DDHH), SKYConditionVisibility, WeatherType, Windspeed, StationPressure, PressureChange and HourlyPrecip.
You have an untrained Azure Machine Learning model that you plan to train to predict
flight delays. You need to assess the variability of the dataset and the reliability of the predictions from the model. Which modules should you use?
Tune Model Hyperparameters
QUESTION: 37 HOTSPOT
You need to use R code in a Transact-SQL statement to merge the repeating values 1 through 6 with Col1 in a table. Which statement should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Microsoft 70-774 Exam (Perform Cloud Data Science with Azure Machine Learning?) Detailed Information
70-774 - Perform Cloud Data Science with Azure Machine Learning?
70-774 Test Objectives
Prepare Data for Analysis in Azure Machine Learning and Export from Azure Machine Learning
Import and export data to and from Azure Machine Learning
Import and export data to and from Azure Blob storage, import and export data to and from Azure SQL Database, import
and export data via Hive Queries, import data from a website, import data from on-premises SQL
Create univariate summaries, create multivariate summaries, visualize univariate distributions, use existing Microsoft
R or Python notebooks for custom summaries and custom visualizations, use zip archives to import external packages
for R or Python
Merge multiple datasets by rows or columns into a single dataset by columns, merge multiple datasets by rows or columns
into a single dataset by rows, add columns that are combinations of other columns, manually select and construct
features for model estimation, automatically select and construct features for model estimation, reduce dimensions
of data through principal component analysis (PCA), manage variable metadata, select standardized variables based
on planned analysis
Develop Machine Learning Models
Select an appropriate algorithm or method
Select an appropriate algorithm for predicting continuous label data, select an appropriate algorithm for supervised
versus unsupervised scenarios, identify when to select R versus Python notebooks, identify an appropriate algorithm
for grouping unlabeled data, identify an appropriate algorithm for classifying label data, select an appropriate
Tune hyperparameters manually; tune hyperparameters automatically; split data into training and testing datasets,
including using routines for cross-validation; build an ensemble using the stacking method
Score and evaluate models, select appropriate evaluation metrics for clustering, select appropriate evaluation metrics
for classification, select appropriate evaluation metrics for regression, use evaluation metrics to choose between
Machine Learning models, compare ensemble metrics against base models
Operationalize and Manage Azure Machine Learning Services
Deploy models using Azure Machine Learning
Publish a model developed inside Azure Machine Learning, publish an externally developed scoring function using an
Azure Machine Learning package, use web service parameters, create and publish a recommendation model, create and
publish a language understanding model
Create projects and experiments, add assets to a project, create new workspaces, invite users to a workspace, switch
between different workspaces, create a Jupyter notebook that references an intermediate dataset
Connect to a published Machine Learning web service, consume a published Machine Learning model programmatically
using a batch execution service, consume a published Machine Learning model programmatically using a request response
service, interact with a published Machine Learning model using Microsoft Excel, publish models to the marketplace
Deploy the appropriate type of HDI cluster, perform exploratory data analysis by using Spark SQL, build and use Machine
Learning models with Spark on HDI, build and use Machine Learning models using MapReduce, build and use Machine
Learning models using Microsoft R Server