That’s not a question but good for her
Confidentiality is a virtue which we need to secure information by limiting computer access to authorized personnel only. People trust us to keep their private matters private. Keeping that confidence is an important aspect of trust.
Answer:
C. consistency, aesthetics
Explanation:
Based on the descriptions given to us in the question we can deduce that the answer is C. consistency, aesthetics. This is because "consistency" is defined as something that always delivers the same results, which is what users need from the interface in order to understand it and continue using it. While "aesthetics" is defined as the visual representation of something (how something will look).
I hope this answered your question. If you have any more questions feel free to ask away at Brainly.
import java.util.Scanner;
public class JavaApplication70 {
public static void main(String[] args) {
Scanner scan = new Scanner(System.in);
System.out.println("Input a String:");
String txt = scan.nextLine();
System.out.println("Input an integer:");
int num = scan.nextInt();
String newTxt = "";
int w = 0;
for (int i = txt.length()-1; i >= 0; i--){
char c = txt.charAt(i);
while (w < num){
newTxt += c;
w++;
}
w = 0;
}
System.out.println(newTxt);
}
}
I hope this helps!
Answer:
4. Supervised learning.
Explanation:
Supervised and Unsupervised learning are both learning approaches in machine learning. In other words, they are sub-branches in machine learning.
In supervised learning, an algorithm(a function) is used to map input(s) to output(s). The aim of supervised learning is to predict output variables for given input data using a mapping function. When an input is given, predictions can be made to get the output.
Unsupervised learning on the other hand is suitable when no output variables are needed. The only data needed are the inputs. In this type of learning, the system just keeps learning more about the inputs.
Special applications of supervised learning are in image recognition, speech recognition, financial analysis, neural networking, forecasting and a whole lot more.
Application of unsupervised learning is in pre-processing of data during exploratory analysis.
<em>Hope this helps!</em>
