The article is devoted to the consideration of topical issues related to the study of the possibility of forecasting the dynamics of stock markets based on neural network models of machine learning. The prospects of applying the neural network approach to building investment forecasts are highlighted. To solve the problem of predicting the dynamics of changes in the value of securities, the problems of training a model on data presented in the form of time series are considered and an approach to the transformation of training data is considered. The method of recursive exclusion of features is described, which is used to identify the most significant parameters that affect price changes in the stock market. An experimental comparison of a number of neural networks was carried out in order to identify the most effective approach to solving the problem of forecasting market dynamics. As a separate example, the implementation of regression based on a radial-basis neural network was considered and an assessment of the quality of the model was presented.

Keywords: stock market, forecast, daily slice, shares, neural network, machine learning, activation function, radial basis function, cross-validation, time series

Search engine optimization allows a website to rank higher in search engines. Through a lot of manipulations on working with the site, you can achieve good results in increasing the conversion of sites. Modern systems for all kinds of data analysis using neural networks can greatly improve the work on this optimization.

Keywords: website promotion, search engine optimization, neural networks, code optimization, convolutional neural networks

In recent years, the use of various tools based on machine learning in the process of writing the source code of various programs, interfaces, and websites has been gaining momentum. These include programs that help in testing applications, programs that analyze the developer's code, as well as assistant programs that help write code right in the process, predicting and prompting the developer with options for the finished program code. In this article, just the same, such assistant programs will be considered in order to analyze the shortcomings and justify the need to develop functionality in this direction.

Keywords: source code, machine learning, neural networks, application testing problem, natural language processing

This article describes the formation of a training set for training language neural networks for their use in tasks related to the analysis and search for matches and / or correspondences in meaning / value, and specifically with functions and methods in the source code of a programming language. The key parameters required in the sample for the correct training of the neural network are determined.

Keywords: source code, machine learning, natural language processing, neural network, data analysis

The paper discusses improvement of approach to voice recognition for editing source code, using Google Cloud Speech. The improved approach combines neural networks with sound editing, editing distances, and replacement tables. The architecture for the recognition of Python language expressions is suggested. The results of the analysis of the testing approach on prototype program, that combines editing code on GitHub with Telegram, is discussed, The paper discusses advantages and disadvantages of the improved approach.

Keywords: voice recognition, neural networks, machine learning, source code analysis, formal languages, editing distances

This article proposes the development of a method for transmitting secure messages using a combination of best practices for organizing data exchange and cryptographic instant messaging protocols using end-to-end encryption. It considers ways of organizing an application using a peer-to-peer network and client-server architecture. It analyzes popular instant messaging protocols using end-to-end encryption. The software components of the application based on the developed method are described.

Keywords: messenger, end-to-end encryption, cryptographic protocol, instant messaging, peer-to-peer network, client-server