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NEW QUESTION: 1
Which properties does ECC Master Production Scheduling (MPS) have? (Choose three.)
A. MPS items can be defined on MRP Area level (Material Requirements Planning Area).
B. MPS items can be taken into consideration by a standard MRP run (Material Requirements Planning).
C. The planning of MPS and Non-MPS items is always carried out in one planning run.
D. Non-MPS items can be taken into consideration by an MPS run.
E. MPS items can be defined on plant level.
Answer: A,D,E

NEW QUESTION: 2
Which printers does the HP UPD support? (Select two.)
A. HP Color LaserJets that support PCL or PostScript
B. HP hostbased LaserJets with Ret
C. non HP printers that support PCL4 and SNMPv2
D. HP LaserJets introduced after 1997
E. all HP Deskjets with PhotoRet IV
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C. Use the ID Types REST API.
D. Use the Ping API.
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NEW QUESTION: 4
Which of the following are examples of hyperparameters? (Select 2 answers.)
A. Number of hidden layers
B. Weights
C. Biases
D. Number of nodes in each hidden layer
Answer: A,D
Explanation:
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