What is Machine Learning?

Machine Learning is a process in which, in the course of solving a large number of similar problems, an analytical system identifies patterns and learns to make further decisions without human intervention. Simply put, machine learning technology is based on searching for patterns in the mass of information and choosing the best solution from the presented ones.

Where is Machine Learning Used?

Most often, machine learning technology is used in marketing. For example, Amazon uses it to show customers the product that they should be interested in. It does this by analyzing data about past purchases and other users.

Google and Yandex also use machine learning in their work to serve ads to specific users. If you have ever noticed that after searching for information about a certain product, you almost immediately saw the corresponding ad in search engines, then this was done thanks to machine learning technologies.

Smart feeds in social networks are arranged in the same way. Analytical systems Facebook, Instagram, Twitter, or TikTok investigate the interests of users by all the data known about them: 

  • viewing posts;
  • likes and comments; 
  • visiting public and groups, etc. 

The higher the user’s activity, the more personalized feed AI selects for him.

In addition, machine learning services are used in medicine and security control structures. In medicine, this is a preliminary diagnosis and selection of an individual treatment plan based on data from the patient’s medical history. And in the field of security – face recognition systems. The machine compares pictures of people from CCTV cameras with pictures of people on the wanted list. With a high resemblance, she gives a signal to the police.

The main tasks that AI performs with the help of machine learning are:

  1. Regression. The system from the array of the presented characteristics predicts the result in the form of a specific figure. For example, this way you can predict how much a Gazprom share will cost in a month or several years, as well as determine the budget for an advertising campaign, etc.
  2. Classification. The system defines the kind of the examined target by a collection of characteristics. For instance, you can recognize spam in emails, or you can recognize what gender a person is in a photo.
  3. Clustering. The system divides the given data display into classes. For example, requests to a corporation from customers can be classified: by promoting causes, kinds of requests, etc.

What is Machine Learning?

There are three types of machine learning:

  • With a teacher (English Supervised machine learning). By “teacher” is meant not a mentor with a pointer, but the idea of human participation in the process of data processing. A certain data array is loaded into the analytical system and the direction for its analysis is set. In this case, the system must confirm or deny any hypothesis.
  • Unsupervised machine learning. In this case, the system “does not know” the correct answers in advance. It only has data, the properties of which you want to find. Thus, the machine independently processes information and finds relationships.
  • Deep learning. This is big data analysis. One computer cannot cope with such a volume of information, so neural networks come to the rescue here. The essence of deep learning is to divide a huge stream of information into small data segments, which are further processed by other devices. It works like this: one processor only collects information on the problem and transfers it further, five other processors analyze this data and transmit the results to the next processors, which are looking for solutions.