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NEW QUESTION: 1
An administrator types in the command router ospf 1 and receives the error message: "OSPF process 1 cannot start." (Output is omitted.) What should be done to correctly set up OSPF?
A. Ensure that the interfaces can ping their directly connected neighbors.
B. Ensure that IP classless is enabled.
C. Ensure that an interface has been configured with an IP address and is up.
D. Ensure that an interface has been configured with an IP address.
Answer: C

NEW QUESTION: 2
金融サービス会社には、証券取引所からの市場データフィードを取り込み、データを変換して、内部のApachi Kafkaクラスターにデータを送信するオンプレミス環境があります。経営陣は、AWSサービスを活用して、一貫したネットワークパフォーマンスを備えたスケーラブルでほぼリアルタイムのソリューションを構築し、株式市場データをアプリケーションに提供したいと考えています。
ソリューションアーキテクトがソリューションを構築するには、どのような手順を踏む必要がありますか？ （3つ選択）
A. オンプレミスのデータセンターからAWSへのAWS Direct Connect接続を確立します。
B. オンプレミスデータセンターからAWSへのサイト間VPNを確立する
C. Amazon EC2 Auto Scalingグループを作成して、オンプレミスのKafkaクラスターからメッセージをプルし、Amazonコンシューマーライブラリを使用してデータをAmazon Kinesisデータストリームに入れます。
D. AWS AppSyncでGraphQL APIを作成し、Amazon Kinesisデータストリームを処理するAWS Lambda関数を作成し、@ connectionsコマンドを使用して、接続されたクライアントにコールバックメッセージを送信します。
E. Amazon EC2 Auto Scalingグループを作成して、オンプレミスのKafkaクラスターからメッセージをプルし、Amazon Kinesisプロデューサーライブラリを使用してデータをKinesisデータストリームに入れます。
F. Amazon API GatewayでWebSocket APIを作成し、Amazon Kinesisデータストリームを処理するAWS Lambda関数を作成し、@ connectionsコマンドを使用して、接続されたクライアントにコールバックメッセージを送信します。
Answer: A,D,F

NEW QUESTION: 3
A Machine Learning Specialist is building a prediction model for a large number of features using linear models, such as linear regression and logistic regression During exploratory data analysis the Specialist observes that many features are highly correlated with each other This may make the model unstable What should be done to reduce the impact of having such a large number of features?
A. Use matrix multiplication on highly correlated features.
B. Create a new feature space using principal component analysis (PCA)
C. Perform one-hot encoding on highly correlated features
D. Apply the Pearson correlation coefficient
Answer: C