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NEW QUESTION: 1
You need to implement Role1.
Which command should you run before you create Role1? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION: 2
A. Option B
B. Option A
C. Option C
D. Option D
Answer: B
NEW QUESTION: 3
一連のラベル付き写真を使用するマルチクラス画像分類の深層学習モデルがあります。次のコードを作成して、モデルをトレーニングするときにハイパーパラメーター値を選択します。
次の各ステートメントについて、ステートメントがtrueの場合は[はい]を選択します。それ以外の場合は、[いいえ]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: Yes
Hyperparameters are adjustable parameters you choose to train a model that govern the training process itself. Azure Machine Learning allows you to automate hyperparameter exploration in an efficient manner, saving you significant time and resources. You specify the range of hyperparameter values and a maximum number of training runs. The system then automatically launches multiple simultaneous runs with different parameter configurations and finds the configuration that results in the best performance, measured by the metric you choose. Poorly performing training runs are automatically early terminated, reducing wastage of compute resources. These resources are instead used to explore other hyperparameter configurations.
Box 2: Yes
uniform(low, high) - Returns a value uniformly distributed between low and high Box 3: No Bayesian sampling does not currently support any early termination policy.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
NEW QUESTION: 4
Refer to the exhibit. Which interoperability technique implemented on the dual-stack routers would allow connectivity between IPv6 sites across automatic created tunnels using the 2002::/16 prefix?
A. NAT-PT
B. ISATAP tunnel
C. 6to4 tunnel
D. GRE tunnel
E. Dual Stack
Answer: C
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