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NEW QUESTION: 1
Which of the following are examples of hyperparameters? (Select 2 answers.)
A. Number of nodes in each hidden layer
B. Biases
C. Number of hidden layers
D. Weights
Answer: A,C
Explanation:
If model parameters are variables that get adjusted by training with existing data, your hyperparameters are the variables about the training process itself. For example, part of setting up a deep neural network is deciding how many "hidden" layers of nodes to use between the input layer and the output layer, as well as how many nodes each layer should use. These variables are not directly related to the training data at all. They are configuration variables. Another difference is that parameters change during a training job, while the hyperparameters are usually constant during a job.
Weights and biases are variables that get adjusted during the training process, so they are not hyperparameters.
Reference: https://cloud.google.com/ml-engine/docs/hyperparameter-tuning-overview

NEW QUESTION: 2
You are designing a Cisco UCS environment that requires RSA SecurlD for user authentication. Which authentication method must you include in the design?
A. a local Cisco UCS user database
B. client certificate authentication
C. RADIUS authentication
D. LDAP authentication
Answer: C

NEW QUESTION: 3
Which of the following is mandatory for a Notification object to contain? (Choose three.)
A. A detail text.
B. A small icon
C. A notification sound
D. A title
Answer: A,B,D