Answer:
Your answer is D. multimedia software
Explanation:
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>
Answer:
Hence, <u>Input Validation</u> is the process of inspecting data that has been input to a program to make sure it is valid before using it in a computation.
Explanation:
The input should be validated before further processing to avoid problems in execution of program afterwards.
The process of input validation is defined to make sure that the input is valid.
Hence, <u>Input Validation</u> is the process of inspecting data that has been input to a program to make sure it is valid before using it in a computation ..
