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NEW QUESTION: 1
Which three choices are determined by including the customer's networking staff in an IBM Tivoli Storage Manager (TSM) V7.1 pre-implementation planning meeting?
A. Is the client option PRESCHEDULECMD necessary?
B. Are nightly archives of specific files necessary?
C. Which TSM components need to be configured for communication through a firewall?
D. Is journal-based backup an appropriate choice for deployment?
E. Is SSL required for client-server communications?
F. Is TSM for SAN an appropriate choice for deployment?
Answer: C,E,F
NEW QUESTION: 2
.What is an edit check to determine whether a field contains valid data?
A. Reasonableness check
B. Accuracy check
C. Redundancy check
D. Completeness check
Answer: D
Explanation:
A completeness check is an edit check to determine whether a field contains valid datA .
NEW QUESTION: 3
Which of the following are examples of hyperparameters? (Select 2 answers.)
A. Biases
B. Number of hidden layers
C. Weights
D. Number of nodes in each hidden layer
Answer: B,D
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