The urgency of the topic is the integration of machine learning technologies into cybersecurity systems. After getting acquainted with the technical literature, the main technologies of machine learning that are implemented in the organization of cybersecurity were formulated. Acquainted with the main type of artificial neural network used in the prevention and detection of cyber threats and found that the main to consider the general application of machine learning technologies are artificial neural networks based on a multilayer perceptron with inverse error propagation. It is proposed to use indicators of compromise cyberattacks as initial information for automatic machine learning systems. Emphasis is placed on the main types of data that can be used by surveillance subsystems for information security and cybersecurity to perform tasks and prevent, classify and predict cybersecurity events. According to the results of the analysis, the main problem areas for their implementation in information security systems are identified. The problem of using machine learning (ML) in cybersecurity is difficult to solve, because advances in this area open up many opportunities, from which it is difficult to choose effective means of implementation and decision-making. In addition, this technology can also be used by hackers to create a cyber attack. The purpose of the study is to implement machine learning in information security and cybersecurity technology, and to depict a model based on self-learning

This article analyzes existing supplements that help people monitor their health and nutrition, and reveals important current issues that have received little attention so far. Eating disorders also include some developmental abnormalities that can be prevented by diet, disorders that respond to dietary treatment, food allergies and intolerances, potential food hazards, and the interaction of food and nutrients with medications. This web application is for people who have special diets due to illness, doctors' recommendations. The implementation involves analyzing the possibilities of developing a software system that allows you to track meals, give advice on diet planning and recommend recipes and products for the user's health indicators to be adjusted. Potential users of this software product will be primarily patients with eating disorders, but also those who simply need to change their diet for one reason or another, such as allergies, diabetics, etc. To control their diet, you can use a variety of tools that differ from each other in the degree of convenience and accessibility. The easiest way to control is to independently count the food eaten and record information about them. Today, there are many applications, both mobile and web applications, that are designed to monitor diet, pick up recipes or keep a diary of meals. The health nutrition web application is designed primarily to monitor your health and the fullness of all the necessary components of the food you eat, as recommended by your doctor. The essence of the application is that the user enters his basic data such as gender, age, height, weight, and optionally, for more accurate and useful recommendations, the presence of allergies, the presence of diseases or genetic predisposition to them, food preferences, increased / reduced test results (which may be affected by nutrition), recommendations of doctors, etc.