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NEW QUESTION: 1
The following is a network diagram for a project.
The critical path for the project is how many days in duration?
A. 0
B. 1
C. 2
D. 3
Answer: C
NEW QUESTION: 2
What component on the blockchain maintains the "world state"?
A. Distributed Ledger
B. .bna
C. .acl
D. Reputation Manager
Answer: A
Explanation:
Explanation
Distributed Ledger manages the world state and the transaction log in the blockchain. The world state is defined as the state of all transactions on the Blockchain, where all nodes agree that all blocks on the Blockchain are at the same state. It implements three key attributes. It efficiently calculates the cryptographic hash of the entire dataset of each block. It efficiently transmits a minimal "delta" changes to the dataset, when a peer is out of sync and needs to "catch up". It minimizes the amount of stored data required for each peer to operate.
NEW QUESTION: 3
You do a Student's t-test to compare the average test scores of sample groups from populations A and B. Group A averaged 10 points higher than group B. You find that this difference is significant,
with a p-value of 0.03. What does that mean?
A. There is a 3% chance that a sample group from population A will score 10 points higher that a sample group from population B.
B. The difference in scores between a sample from population A and a sample from population B will tend to be within 3% of 10 points.
C. There is a 97% chance that a sample group from population A will score 10 points higher that a sample group from population B.
D. There is a 3% chance that you have identified a difference between the populations when in reality there is none.
Answer: D
NEW QUESTION: 4
Azure Container Instanceにモデルをデプロイします。
モデルAPIを呼び出すには、Azure Machine Learning SDKを使用する必要があります。
ネイティブSDKクラスおよびメソッドを使用して、デプロイされたモデルを呼び出す必要があります。
コマンドをどのように完了する必要がありますか？回答するには、回答領域で適切なオプションを選択します。
注：それぞれの正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: from azureml.core.webservice import Webservice
The following code shows how to use the SDK to update the model, environment, and entry script for a web service to Azure Container Instances:
from azureml.core import Environment
from azureml.core.webservice import Webservice
from azureml.core.model import Model, InferenceConfig
Box 2: predictions = service.run(input_json)
Example: The following code demonstrates sending data to the service:
import json
test_sample = json.dumps({'data': [
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
[10, 9, 8, 7, 6, 5, 4, 3, 2, 1]
]})
test_sample = bytes(test_sample, encoding='utf8')
prediction = service.run(input_data=test_sample)
print(prediction)
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/how-to-deploy-azure-container-instance
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-deployment
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