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NEW QUESTION: 1
John wants to upgrade his IBM WebSphere Portal 8.0 server that does not contain IBM Web Content Manager to one that does include Web Content Manager. To do this, John can:
A. Run the following ConfigEngine.sh upgrade-profile -DUpgradeServerToContent=true.
B. Run the following ConfigEngine.sh upgrade-server-to-content-migration -DUpgradeServerToContent=true.
C. The migration is not supported from different version of WebSphere Portal server.
D. Run the following ConfigEngine.sh upgrade-profile.
Answer: A
NEW QUESTION: 2
Welche zwei Arten von Tags werden heute in RFID verwendet? Es gibt 2 richtige Antworten auf diese Frage.
A. Passiv
B. Aktiv
C. Fest verdrahtet
D. Lokal
E. CPU-direkt
Answer: A,B
NEW QUESTION: 3
A. 192.168.20.10
B. 224.0.0.10
C. 192.168.1.10
D. 192.168.10.10
E. 169.254.0.10
F. 192.168.2.10
Answer: C,D
Explanation:
* Scenario:
/ Assign a static IP address to DAG1.
/ A database availability group (DAG) named DAG1 that contains EX2, EX3, EX5, and
EX6. DAG1 is configured to use DHCP to obtain an IP address.
/ Subnet 192.168.1.0/24 and subnet 192.168.10.0/24 are assigned as the MAPI network.
* A DAG network is a collection of one or more subnets used for either replication traffic or MAPI traffic. Each DAG contains a maximum of one MAPI network and zero or more replication networks.
NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario. Each question in 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 a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
Note: Data used in pipeline can be produced by one step and consumed in another step by providing a PipelineData object as an output of one step and an input of one or more subsequent steps.
Compare with this example, the pipeline train step depends on the process_step_output output of the pipeline process step:
from azureml.pipeline.core import Pipeline, PipelineData
from azureml.pipeline.steps import PythonScriptStep
datastore = ws.get_default_datastore()
process_step_output = PipelineData("processed_data", datastore=datastore) process_step = PythonScriptStep(script_name="process.py", arguments=["--data_for_train", process_step_output], outputs=[process_step_output], compute_target=aml_compute, source_directory=process_directory) train_step = PythonScriptStep(script_name="train.py", arguments=["--data_for_train", process_step_output], inputs=[process_step_output], compute_target=aml_compute, source_directory=train_directory) pipeline = Pipeline(workspace=ws, steps=[process_step, train_step]) Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azu