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NEW QUESTION: 1
Which of the following are examples of hyperparameters? (Select 2 answers.)
A. Weights
B. Number of hidden layers
C. Number of nodes in each hidden layer
D. Biases
Answer: B,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
requirement must be met when expanding a VxRail G560F 3 node Cluster with a 4ih G Series node in the same chassis?
A. Node must be identical to the other three nodes
B. Node must be a hybrid node
C. Node requires only the same drive configuration
D. Node requires only the same processor type
Answer: A

NEW QUESTION: 3
Which network analysis tool can be used to record packet captures?
A. Wireshark
B. Angry IP Scanner
C. Smart IP Scanner
D. Netman
Answer: A