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NEW QUESTION: 1
管理者は、Amazon Machine Learningサービスを使用して、会社について言及しているソーシャルメディア投稿を2つのカテゴリに分類することを決定しました。応答が必要な投稿とそうでない投稿です。 10,000件の投稿のトレーニングデータセットには、タイムスタンプ、作成者、投稿の全文など、各投稿の詳細が含まれています。トレーニングに必要なターゲットラベルがありません。
どの2つの選択肢が有効なターゲットラベルデータを作成しますか？
A. 2つのクラスの事前確率分布を使用して、モンテカルロシミュレーションを使用してラベルを生成します。
B. センチメント分析NLPライブラリを使用して、投稿に回答が必要かどうかを判断します。
C. Amazon Mechanical Turk Webサービスを使用して、Turkの従業員に投稿のラベルを付けるように指示するヒューマンインテリジェンスタスクを公開します。
D. ソーシャルメディア処理チームに各投稿を確認してラベルを提供するよう依頼してください。
Answer: C,D
Explanation:
You need accurate data to train the service and get accurate results from future data. The options described in B and D would end up training an ML model using the output from a different machine learning model and therefore would significantly increase the possible error rate. It is extremely important to have a very low error rate (if any!) in your training set, and therefore human-validated or assured labels are essential.
It is essential when writing mobile applications that you consider the security of both how the application

NEW QUESTION: 2
What is the default setting of Advanced Deduplication when Data Reduction is selected within Unisphere?
A. Disabled for thin LUNs in an All-Flash pool
B. Disabled for thick LUNs and enabled for thin LUNs
C. Enabled for both thick and thin LUNs
D. Enabled for thin LUNs in an All-Flash pool
Answer: D

NEW QUESTION: 3

A. SwitchCisc0
B. SwitchCisco
C. Switch-Cisco!
D. Switch-Cisco
Answer: A