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The article examines approaches to developing a front-end framework for creating web applications with an adaptive graphical interface that dynamically adjusts to the individual needs of users through machine learning algorithms. The relevance of the problem lies in the need to develop interfaces capable of simultaneously meeting the needs of different demographic groups, which requires flexibility in customizing the user experience (UX) and user interface (UI) of modern websites.

Ensemble methods can be used for many tasks, some of the most popular being: classification, regression, and image segmentation. Image segmentation is a challenging task, where the use of ensemble machine learning methods provides an opportunity to improve the accuracy of neural network predictions.

Due to the simplification of the processes of creating and distributing news via the Internet, as well as due to the physical impossibility of checking large volumes of information circulating in the network, the volume of disinformation and fake news distribution has increased significantly. A decision support system for identifying disinformation, fakes and propaganda based on machine learning has been built. The method of news text analysis for identifying fakes and predicting the detection of disinformation in news texts has been studied.

In the era of rapid technological advancement, when robotics and intelligent systems are becoming an integral part of everyday life, the importance of developing control systems for mobile robotic platforms using artificial neural networks becomes extremely high and relevant. This field not only has significant practical needs but also holds considerable potential for innovative development. The evolution of modern robotics and computational intelligence has necessitated the creation of more efficient and adaptive mobile robotic systems.

The article describes a study of identification of fake news based on natural language processing, big data analysis and deep learning technology. The developed system automatically checks the news for signs of fake news, such as the use of manipulative language, unverified sources and unreliable information. Data visualization is implemented on the basis of a friendly user interface that displays the results of news analysis in a convenient and understandable format.

The peculiarities of the use of the harmonized system of description and coding of goods, the harmonized tariff system of codes in modern customs classification systems are analyzed. Special attention is paid to the challenges that arise when applying these codes, in particular due to the complexity of the product nomenclature, as well as the variety of product descriptions. In addition, the possibilities of integrating IT technologies, machine learning and artificial intelligence methods to automate and optimize customs classification procedures are being explored.

The study substantiates the feasibility of using machine learning technology to improve the iteration planning process in IT projects implemented using the Scrum methodology. The problem of productivity planning in teams is set. The subject and object of the research are formulated. The expected scientific novelty and practical significance of the research results are described. A range of potential issues related to task planning in IT projects, particularly the accuracy of team productivity forecasting, is considered.

This article discusses the practical aspects of applying logistic regression for binary data classification. Logistic regression determines the probability of an object belonging to one of two classes. This probability is calculated with the help of a sigmoid function, the argument of which is a linear convolution of the feature vector of the object with the weighting coefficients obtained during the minimization of the logarithmic loss function. Predicted class labels are determined by comparing the calculated probability with a given threshold value.

In today’s world, where the speed of technological change is extremely impressive, the traffic industry is not left behind. The use of lane segmentation on the road is becoming a key element not only for safety, but also for improving navigation and traffic sign detection systems. This approach opens the door to a new level of efficiency and accuracy in traffic management, helping to improve the quality and safety of our movement. Let’s dive into the details of this exciting and promising area of road transport technology development.