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NEW QUESTION: 1
Which of the following interfaces is not using the GTP-C protocol?
A. The S5 interface
B. The S8 interface
C. The S1-MME interface
D. The S10 interface
E. TheS11 interface
Answer: C

NEW QUESTION: 2
モデルの適合の問題を修正する必要があります。
順番に実行する必要がある3つのアクションはどれですか?回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。

Answer:
Explanation:

Explanation:
Step 1: Augment the data
Scenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers.
Step 2: Add the Bayesian Linear Regression module.
Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.
Step 3: Configure the regularization weight.
Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.
Scenario:
Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.
Incorrect Answers:
Multiclass Decision Jungle module:
Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs).
L-BFGS:
L-BFGS stands for "limited memory Broyden-Fletcher-Goldfarb-Shanno". It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.
References:
<https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession>

NEW QUESTION: 3
You store data in an Azure SQL data warehouse.
You need to design a solution to ensure that the data warehouse and the most current data is available within one hour of a datacenter failure.
Which three actions should you include in the design? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Each day, restore the data warehouse from a geo-redundant backup to an available Azure region.
B. If a failure occurs, update the connection strings to point to the recovered data warehouse.
C. If a failure occurs, modify the Azure Firewall rules of the data warehouse.
D. Each day, create Azure Firewall rules that allow access to the restored data warehouse.
E. Each day, restore the data warehouse from a user-defined restore point to an available Azure region.
Answer: B,D,E
Explanation:
E: You can create a user-defined restore point and restore from the newly created restore point to a new data warehouse in a different region.
Note: A data warehouse snapshot creates a restore point you can leverage to recover or copy your data warehouse to a previous state.
A data warehouse restore is a new data warehouse that is created from a restore point of an existing or deleted data warehouse. On average within the same region, restore rates typically take around 20 minutes.
Incorrect Answers:
A: SQL Data Warehouse performs a geo-backup once per day to a paired data center. The RPO for a geo-restore is 24 hours. You can restore the geo-backup to a server in any other region where SQL Data Warehouse is supported. A geo-backup ensures you can restore data warehouse in case you cannot access the restore points in your primary region.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore

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