A .jpg file is going to be a picture. =)
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>
The RAM memory of a computer contains the volatile memory, which includes; Websites recently visited
<h3>Random Access Memory(RAM)</h3>
Random access memory (RAM) is defined as a computer's short-term memory that it utilizes to handle all active tasks and applications.
Now, no single program, file, game, or stream would work without a RAM. Thus, RAM is a temporary storage that goes away when we shut down the computer.
Examples of things that RAM store from the options given is only websites visited recently.
Read more about Random Access Memory at; brainly.com/question/86807
