Machine learning is an area of computer science that means 'machine learning'.
It is part of the concept of artificial intelligence, which studies ways for machines to perform tasks that would be performed by people.
It is a programming used in computers, formed by pre-defined rules that allow computers to make decisions based on previous data and data used by the user.
According to programs made, the computer has the ability to make decisions that can solve problems or boost publications on the internet, for example.
How does machine learning work?
The basis of operation are the algorithms, which are defined sequences composed of information and instructions that will be followed by the computer.
These sequences allow computers to make a decision according to the situation and the information that has been entered into it.
It is the algorithm that carries information about how certain procedures and operations should be done or about how an action should be performed.
There are several types of application and programming languages for using algorithms. They vary according to the need that will be met or the purpose of the algorithm created.
Types of machine learning
There are two main types of machine learning: supervised learning and unsupervised learning.
supervised learning
In supervised learning, there is a previous set of data entered in the machine and the suggestions that will be given to the user must be similar to the registered data.
Basically the information is used to predict an expected result by the user or to classify the elements used.
Example: a photograph is placed in the internet browser, which searches to find information about the origin of the image or other similar images.
unsupervised learning
In unsupervised learning there is no specific expected result, that is, it is not possible to predict the results of the crossing of information.
In this type of learning, the data are grouped and the results change according to the variables.
Example: in a library search engine it is possible to get varied results. Changing the results depends on the type of search performed and the variables that are used, such as book name, author name or publication date.
See also the meaning of Artificial intelligence.
What is machine learning for?
Machine learning can be used for many functions. One of the most used nowadays is in social media, internet search and digital marketing.
For example, machine learning algorithms are used to make suggestions to an internet user. They are used in e-commerce websites, social networks, games, video storage platforms and music playback applications.
In this case, the algorithm uses your sequence data and internet browsing history data to make new suggestions to the user. User preferences during browsing and data sharing are used to suggest programs or services that are similar.
These are more common uses, but machine learning knowledge can also be applied to many other situations, such as:
- internet searches,
- data collection and analysis,
- tracking spam messages,
- organization and classification of information,
- search for fraud on the internet.
Difference between machine learning and deep learning
Both machine learning and deep learning are ways of using artificial intelligence. But there is a difference between them because deep learning (which means deep learning) has characteristics more similar to the human learning capacity.
Deep learning also uses the prediction of results from established data. The difference is that this happens more precisely, more like what happens in a person's brain because the computer can adapt information more flexibly.
This happens because in deep learning an artificial neural network is created, which functions similar to the network of neurons in the human brain.
It is this network that makes the functioning of the machine have many similarities with the functioning of the brain and is able to learn and interpret information.
See also the meanings of software and Bitcoin.