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NEW QUESTION: 1

A. Option A
B. Option D
C. Option B
D. Option C
Answer: D

NEW QUESTION: 2
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:
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=azure-ml-py

NEW QUESTION: 3
Depending on configuration, which of the following two behaviors can the ASA classifier exhibit when
receiving unicast traffic on an interface shared by multiple contexts? (Choose two.)
A. Traffic is classified using the destination address of the packet using the NAT table.
B. Traffic is classified using the destination MAC address of the packet.
C. Traffic is classified by copying and sending the packet to all the contexts.
D. Traffic is classified using the destination address of the packet using the connection table.
E. Traffic is classified using the destination address of the packet using the routing table.
Answer: A,B

NEW QUESTION: 4
During inspection of your Threat Prevention logs you find four different computers having one event each
with a Critical Severity. Which of those hosts should you try to remediate first?
A. Host having a Critical event found by Antivirus
B. Host having a Critical event found by Threat Emulation
C. Host having a Critical event found by IPS
D. Host having a Critical event found by Anti-Bot
Answer: D