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NEW QUESTION: 1
Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective?
A. Use feature engineering to add features for eyes, noses, and mouths to the input data.
B. Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.
C. Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.
D. Use K-means Clustering to detect faces in the pixels.
Answer: C
Explanation:
Traditional machine learning relies on shallow nets, composed of one input and one output layer, and at most one hidden layer in between. More than three layers (including input and output) qualifies as "deep" learning. So deep is a strictly defined, technical term that means more than one hidden layer.
In deep-learning networks, each layer of nodes trains on a distinct set of features based on the previous layer's output. The further you advance into the neural net, the more complex the features your nodes can recognize, since they aggregate and recombine features from the previous layer.
A neural network with only one hidden layer would be unable to automatically recognize high-level features of faces, such as eyes, because it wouldn't be able to "build" these features using previous hidden layers that detect low-level features, such as lines. Feature engineering is difficult to perform on raw image data.
K-means Clustering is an unsupervised learning method used to categorize unlabeled data.
Reference: https://deeplearning4j.org/neuralnet-overview

NEW QUESTION: 2
A Symmetrix VMAX 40K customer intends to use EMC Virtual Storage Integrator in their VMware vSphere environment. Which VSI feature will allow them to extend a VMFS datastore with a new Symmetrix thin device?
A. Path Management
B. Storage Viewer
C. Storage Pool Management
D. Unified Storage Management
Answer: D

NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You network contains an Active Directory forest named contoso.com. The forest contains a child domain named eu.contoso.com.
You plan to implement live migration between two Hyper-V hosts that run Windows Server 2016. The hosts are configured as shown in the following table.

You need to ensure that you can perform a live migration of VM1 from Host1 to Host2.
Solution: You replace the processor in Host1 with a processor that is identical to the processor in Host2.
Does meet the goal?
A. Yes
B. No
Answer: B

NEW QUESTION: 4
프로젝트 실행 단계에서 프로젝트 구성원의 의견 불일치가 빈번합니다. 그 결과 프로젝트가 예산을 초과하고 일정이 늦어지고 있습니다. 프로젝트 관리자는 주관적인 아이디어를 기반으로 프로젝트 커뮤니케이션을 수행하고 다른 팀 구성원의 의견을 고려하지 않습니다. 프로젝트 관리자는 또한 팀원이 내부 학습 플랫폼을 설정한다는 아이디어에 반대합니다.
프로젝트 관리자는 어떤 커뮤니케이션 방법을 사용합니까?
A. 밀기
B. 대화 형
C. 당기기
D. 독립
Answer: B