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NEW QUESTION: 1
ランディングページのレイアウトテンプレートに使用できる変数タグはどれですか？
（3つの回答を選択してください）
A. %% content %%
B. %% tittle %%
C. %% description %%
D. %% form %%
E. %% name %%
Answer: A,B,C
NEW QUESTION: 2
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:
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: 3
A. Option B
B. Option A
C. Option C
D. Option D
Answer: D
Explanation:
When the user has configured Transmission Control Protocol (TCP) or Secure Sockets Layer (SSL) for
both front-end and back-end connections of the Elastic Load Balancer, the load balancer forwards the
request to the back-end instances without modifying the request headers unless the proxy header is
enabled. If the end user is requesting from a Proxy Protocol enabled proxy server, then the ELB admin
should not enable the Proxy Protocol on the load balancer. If the Proxy Protocol is enabled on both the
proxy server and the load balancer, the load balancer will add another header to the request which
already has a header from the proxy server. This duplication may result in errors.
Reference:
http://docs.aws.amazon.com/ElasticLoadBalancing/latest/DeveloperGuide/enable-proxy-protocol.html
