Answer:
c. NSTISSI No. 4011
Explanation:
NSTISSI is an acronym for National Security Telecommunications and Information Systems Security Institute.
It is one of the standards set by the Committee on National Security Systems (CNSS), an intergovernmental agency saddled with the responsibility of setting policies for the security of the IT (information technology) security systems of the United States of America.
NSTISSI No. 4011 presents a comprehensive model for information security and is becoming the evaluation standard for the security of information systems.
Generally, all information technology institutions and telecommunications providers are required by law to obtain a NSTISSI-4011 certification or license because it is a standard for Information Systems Security (INFOSEC) professionals.
Answer:
b) A separate part of the program that performs a specific task.
Explanation:
A subroutine is a portion of the program that can be invoked to perform a specific task. Typically, it performs that task and returns execution control to the point immediately following its invocation. It may or may not maintain "history" or "state", and it may or may not throw exceptions.
A well-behaved subroutine will only operate on data passed to it, will not maintain any internal history or state, and will have only one exit.
Answer:
def SwapMinMax ( myList ):
myList.sort()
myList[0], myList[len(myList)-1] = myList[len(myList)-1], myList[0]
return myList
Explanation:
By sorting the list, you ensure the smallest element will be in the initial position in the list and the largest element will be in the final position of the list.
Using the len method on the list, we can get the length of the list, and we need to subtract 1 to get the maximum element index of the list. Then we simply swap index 0 and the maximum index of the list.
Finally, we return the new sorted list that has swapped the positions of the lowest and highest element values.
Cheers.
Answer:
DEEP LEARNING
Before looking into the code, some things that are good to know: Both TensorFlow and PyTorch are machine learning frameworks specifically designed for developing deep learning algorithms with access to the computational power needed to process lots of data (e.g. parallel computing, training on GPUs, etc).
Explanation:
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