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NEW QUESTION: 1
Refer to the exhibit:
A network support engineer tests the DHCP scopes design for a wireless network. The engineer finds that clients connected to the Guest SSID not get the IP address as per the design. Guests that are mapped to VLAN
1000 should get the IP address form the local controller's DHCP. As per the company policy, guests cannot get the IP form the controller DHCP.
Based on the information shown in the exhibit, what does the engineer need to do the correct this?
A. Change the VLAN 1000 IP address.
B. Change the VLAN 1000 name and DHCP pool name so they are the same.
C. Change the VLAN 1000 subnet mask.
D. Change port GE0/0/0 to allow VLAN 1000.
Answer: B
NEW QUESTION: 2
Which of the following ports need to be open on the Firewall for an Agent Handler to communicate with ePO and database server(s) inside of a network? (Choose two)
A. Port 1433
B. Port 80
C. Port 8081
D. Port 8082
E. Port 8445
Answer: A,B
NEW QUESTION: 3
You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment.
You need to configure the module. You must meet the following requirements:
* Divide the data into subsets
* Assign the rows into folds using a round-robin method
* Allow rows in the dataset to be reused
How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Use the Split data into partitions option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.
* Add the Partition and Sample module to your experiment in Studio (classic), and connect the dataset.
* For Partition or sample mode, select Assign to Folds.
* Use replacement in the partitioning: Select this option if you want the sampled row to be put back into the pool of rows for potential reuse. As a result, the same row might be assigned to several folds.
* If you do not use replacement (the default option), the sampled row is not put back into the pool of rows for potential reuse. As a result, each row can be assigned to only one fold.
* Randomized split: Select this option if you want rows to be randomly assigned to folds.
If you do not select this option, rows are assigned to folds using the round-robin method.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample