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NEW QUESTION: 1
Which three of these AP working modes is able to detect rogue access points over the air rather than through the wired network? (Choose three.)
A. rogue discovery mode
B. FlexConnect mode
C. local mode
D. monitor mode
E. sniffer mode
F. rogue detector mode
Answer: B,C,D
NEW QUESTION: 2
Azure Search 인덱서의 구성을 확인하고 있습니다.
서비스는 데이터 가져 오기 옵션을 사용하는 인덱서로 구성되었습니다. 색인은 색인 구성 전시에 표시된 옵션을 사용하여 구성됩니다. (인덱스 구성 탭을 클릭하십시오.)
가져 오기 작업의 데이터 소스로 Azure 테이블을 사용합니다. 테이블에는 스토리지 데이터 전시회의 필드와 일치하는 항목 재고 데이터가 있는 세 개의 레코드가 있습니다. 이 레코드는 인덱스를 만들 때 가져 왔습니다. (저장소 데이터 탭을 클릭하십시오.) 사용자가 필터없이 검색하면 세 개의 레코드가 모두 표시됩니다.
사용자가 설명별로 항목을 검색하면 검색 탐색기가 레코드를 리턴하지 않습니다. 검색 탐색기 전시회에는 테스트에 대한 쿼리 및 결과가 표시됩니다. 테스트에서 사용자는 bag이라는 단어가 포함 된 설명이 있는 테이블의 모든 항목을 검색하려고 합니다. (검색 탐색기 탭을 클릭하십시오.)
문제를 해결해야합니다.
다음 각 명령문에 대해 명령문이 참이면 예를 선택하십시오. 그렇지 않으면 아니오를 선택하십시오.
참고 : 각각의 올바른 선택은 1 포인트의 가치가 있습니다.
Answer:
Explanation:
설명:
상자 1 : 그렇습니다
항목 설명 필드를 검색 할 수 없습니다.
상자 2 : 아니오
ItemDescription 필드는 검색 할 수 없지만 인덱스를 다시 만들어야 합니다.
상자 3 : 그렇습니다
Azure Search의 인덱서는 외부 Azure 데이터 원본에서 검색 가능한 데이터와 메타 데이터를 추출하고 인덱스와 데이터 원본 간의 필드 간 매핑을 기반으로 인덱스를 채웁니다. 이 방법은 인덱스에 데이터를 추가하는 코드를 작성하지 않아도 서비스가 데이터를 가져 오기 때문에 '풀 모델'이라고도 합니다.
상자 4 : 아니다
References:
https://docs.microsoft.com/en-us/azure/search/search-what-is-an-index
https://docs.microsoft.com/en-us/azure/search/search-indexer-overview
NEW QUESTION: 3
You have a functioning end-to-end ML pipeline that involves tuning the hyperparameters of your ML model using Al Platform, and then using the best-tuned parameters for training. Hypertuning is taking longer than expected and is delaying the downstream processes. You want to speed up the tuning job without significantly compromising its effectiveness. Which actions should you take?
Choose 2 answers
A. Decrease the number of parallel trials
B. Set the early stopping parameter to TRUE
C. Decrease the range of floating-point values
D. Change the search algorithm from Bayesian search to random search.
E. Decrease the maximum number of trials during subsequent training phases.
Answer: D,E