Answer:
B. Methods and occasionally final attributes
Explanation:
In Computer programming, class members can be defined as the members of a class that typically represents or indicates the behavior and data contained in a class.
Basically, the members of a class are declared in a class, as well as all classes in its inheritance hierarchy except for destructors and constructors.
In a class, member variables are mainly known as its attributes while its member function are seldomly referred to as its methods or behaviors.
One of the main benefits and importance of using classes is that classes helps to protect and safely guard their member variables and methods by controlling access from other objects.
Therefore, the class members which should be declared as public are methods and occasionally final attributes because a public access modifier can be accessed from anywhere such as within the current or external assembly, as there are no restrictions on its access.
By definition, a neutral network is a set of CPUs which work in parallel in an attempt to simulate the way the human brain works, although in greatly simplified form.
A neutral network processor is a CPU that takes the modeled operation of how a human brain works on a single chip.
Neutral network processors reduce the requirements for brain-like computational processing of entire computer networks that excel in complex applications such as artificial intelligence, machine learning, or computer vision down to a multi-core chip.
In other words, astificial neutral networks are a computational model that consists of a set of units, called artificial neurons, connected to each other to transmit signals. The input information traverses the neutral network (where it undergoes various operations) producing output values. Its name and structure are inspired by the human brain, mimicking the way biological neurons signal each other.
So the goal of the neutral network is to solve problems in the same way as the human brain, although neural networks are more abstract.
In summary, a neutral network is a set of CPUs which work in parallel in an attempt to simulate the way the human brain works, although in greatly simplified form.
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