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NEW QUESTION: 1
RJ-45コネクタはどの2本のピンでデータを送信しますか？ （2つ選んでください）
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: C,E

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:
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 A
B. Option B
C. Option D
D. Option C
Answer: A,D
Explanation:
Explanation
The AWS Documentation mentions the following
By default, AWS OpsWorks Stacks automatically installs the latest updates during setup, after an instance finishes booting. AWS OpsWorks Stacks does not automatically install updates after an instance is online, to avoid interruptions such as restarting application servers. Instead, you manage updates to your online instances yourself, so you can minimize any disruptions.
We recommend that you use one of the following to update your online instances.
Create and start new instances to replace your current online instances. Then delete the current instances. The new instances will have the latest set of security patches installed during setup.
On Linux-based instances in Chef 11.10 or older stacks, run the Update Dependencies stack command, which installs the current set of security patches and other updates on the specified instances.
For more information on Opswork updates, please visit the below url * http://docs.aws.amazon.com/opsworks/latest/userguide/best-practices-updates.htmI