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: well there are many types of software out there and let's use Microsoft for an example there a really protective company so more people would want to buy from Microsoft they have a lot of high-tech computers so and I'm not favoriting Microsoft it's just what I've use Chrome also is really good but you would kind of want to go off like reviews that you see and everything like that because I'm not a big computer tech but that's just what I know
Explanation:
Answer:
Sorting tools allow you to organize data into columns and rows that help you locate what you are looking for.
Explanation:
Spreadsheet applications and relational databases are similar in configuration as they are both arranged in rows and columns (tabular). Sorting a spreadsheet or database is useful as it helps to organize data. A sorted spreadsheet or database can be in ascending or descending order which makes it easier and faster to locate rows of data manually or by query.
