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 The article describes the results of research into the processes of complex analysis of military information based on machine learning and natural language processing to help commanders of tactical units. The system should allow users to have the following capabilities: combining the dictionary and information material, adding terms and abbreviations to the dictionary, classifying objects for radio technical intelligence, visualizing aerial objects, classifying aerial objects, using information materials, organizing information materials.

This article reviews the theoretical aspects of logistic regression for binary data classification, including data preparation processes, training, testing, and model evaluation metrics.

Requirements for input data sets are formulated, methods of coding categorical data are described, methods of scaling input features are defined and substantiated.

In this article, the mathematical justification of logistic regression as an effective and simple to implement method of machine learning is performed.

A review of literary sources was conducted in the direction of statistical processing, analysis and classification of data using the logistic regression method, which confirmed the popularity of this method in various subject areas.

Correct valuation of real estate plays a crucial role in the process of buying and selling. We have carefully studied the existing applications with which we carry out real estate transactions, described their features, advantages and disadvantages. The developed model will help sellers get an estimate of their property according to the parameters entered, which can serve as a starting point for establishing the final value.

A method for recognizing contours of objects in a video data stream is proposed. Data will be uploaded using a video camera in real time and object recognition will be performed. We will use the YOLO network – a method of identifying and recognizing objects in real time. Recognized objects will be recorded in a video sequence showing the contours of the objects.

In the article, the authors analyze the current state of research in the field of emotional analysis of Ukrainian-language content for data mining systems. The main methods and approaches to solving the problem are analyzed. The main machine learning algorithms for analyzing textual content are also considered. As a result of the analysis, the main methods and approaches that can be used to analyze the Ukrainian language were identified and classified. The next step was to design the system's functionality using a structural approach.

In this article, the authors focused on analyzing the possibilities of using artificial intelligence models for effective detection and analysis of cybercrimes. A comprehensive method using artificial intelligence algorithms, such as Random Forest and Isolation Forest algorithms, is developed and described to detect ransomware, which is one of the main threats to information security management systems (ISMS) in the field of critical infrastructure.

Research focuses on developing an all-encompassing algorithm for efficiently extracting, processing, and analyz- ing data about thermometers. The examination involves the application of a branch of artificial intelligence, in particular machine learning (ML) methods, as a means of automating processes. Such methods facilitate the identification and aggregation of pertinent data, the detection of gaps, and the conversion of unstructured text into an easily analyzable structured format.