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NEW QUESTION: 1
1 - Import the globa model and build the local model using PyTorch.
2 - Build the global model using PyTorch.
3 - Build the global model using TensorFlow.
4 - Import the global model and build the local model using TensorFlow.
Topic 2, Case study
You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering expanding into Europe and has asked you to investigate prices for private residences in major European cities. You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.
There are two datasets in CSV format that contain property details for two cities, London and Paris, with the following columns:
The two datasets have been added to Azure Machine Learning Studio as separate datasets and included as the starting point of the experiment.
The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.
Columns in each dataset contain missing and null values. The dataset also contains many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsinHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.
The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.
You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance.
In each case, the predictor of the dataset is the column named MedianValue. An initial investigation showed that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset.
You must prioritize the columns of data for predicting the outcome. You must use non-parameters statistics to measure the relationships.
You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsinHouse columns.
Given a trained model and a test dataset, you need to compute the permutation feature importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model's accuracy and replicate the findings.
You want to configure hyperparameters in the model learning process to speed the learning phase by using hyperparameters. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.
You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, you need to implement an early stopping criterion on models that provides savings without terminating promising jobs.
You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio. You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each city's main river. The data that identifies that a property is near a river is held in the column named NextToRiver. You want to complete this task before the data goes through the sampling process.
When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.
You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another.
NEW QUESTION: 2
Which Web Services Security (WS-Security) specification maintains a single authenticated identity across multiple dissimilar environments? Click on the correct specification in the image below.
Reference: Java Web Services: Up and Running" By Martin Kalin page 228
NEW QUESTION: 3
You are the system administrator at Contoso, Inc.
You have imported 3 GB of data into an instance, but the storage utilization for your subscription does not reflect the used storage space.
What is causing this discrepancy?
A. You imported the data into a sandbox instance.
B. Custom indexing is enabled on your instance.
C. You imported the data into a preview instance.
D. Data utilization is calculated every 48 hours.
NEW QUESTION: 4
Refer to the exhibit.
A hospital needs an upgrade to 802.1tax for its wireless network. The wireless network supports:
* wireless medical devices
* medical staff voice communicators
* laptops in nurse stations
* medical staff tablets
* visitor and patient personal devices.
All of these devices support both the 2 4GHz and 5GH2 band. Assuming about a max throughput on50 Mbps per AP; the hospital would like. The architect has used VisualRF to plan the AP placement on one of the floors, which the hospital expects will need to suppod about 800 win to deploy APS in stairwells between floors.
How well does the plan meet the requirements?
A. The current AP placement fails to provide adequate signal for the voice communicators in several areas
B. The current AP placement meets coverage requirements, but does not meet capacity requirements.
C. The current AP placement meets the customer requirements in terms of coverage and capacity.
D. The current AP placement fails to account for the lead-lined wails that are common in patient and exam rooms.
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