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NEW QUESTION: 1
Router has wireless and ethernet client interfaces, all client interfaces are bridged. To create a DHCP service for all clients, DHCP server must be configured on:
A. DHCP service is not possible in this setup
B. Ethernet and wireless interfaces
C. Only on the bridge interface
D. Every bridge port
Answer: C
NEW QUESTION: 2
SIMULATION
What are the 3 levels of access available through Organization-wide Defaults?
Answer:
Explanation:
Public Read/write - View and edit all records Public Read Only - View all records Private
- View only own records
NEW QUESTION: 3
You are using the Azure Machine Learning Service to automate hyperparameter exploration of your neural network classification model.
You must define the hyperparameter space to automatically tune hyperparameters using random sampling according to following requirements:
The learning rate must be selected from a normal distribution with a mean value of 10 and a standard deviation of 3.
Batch size must be 16, 32 and 64.
Keep probability must be a value selected from a uniform distribution between the range of 0.05 and 0.1.
You need to use the param_sampling method of the Python API for the Azure Machine Learning Service.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
In random sampling, hyperparameter values are randomly selected from the defined search space. Random sampling allows the search space to include both discrete and continuous hyperparameters.
Example:
from azureml.train.hyperdrive import RandomParameterSampling
param_sampling = RandomParameterSampling( {
"learning_rate": normal(10, 3),
"keep_probability": uniform(0.05, 0.1),
"batch_size": choice(16, 32, 64)
}
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters