python

Gender recognition from voice is a challenging problem in speech processing. This task involves extracting meaningful features from speech signals and classifying them into male or female categories. In this article, was implemented a gender recognition system using Python programming. I first recorded voice samples from both male and female speakers and extracted Mel-frequency cepstral coefficients (MFCC) as features. Then trained, a Support Vector Machine (SVM) classifier was on these features and evaluated its performance using accuracy, precision, recall, and F1-score metrics.

The work is dedicated to the development of a mobile chatbot containing an information currency converter, designed for use by a wide range of people. A chatbot is a subject-oriented text-based dialog interface that allows a user to perform a limited set of tasks: getting information about the current rate of currencies (USD or EUR) relative to the national currency and finding out the current rate of cryptocurrencies (Bitcoin, Ethereum, Litecoin) in dollars or euros.

The article investigates the system for contactless payments using NFC technology. The practice of acquiring as a method of trade that increases the attractiveness of the business for the client and simplifies the process of trade for owners and employees. The relevance of such a system in Ukraine and prospects for its development are determined.

The goal of the work is to develop a software system for motion detection of and tracking object. It consists of the user interface which is presented as a desktop application. This paper describes the process of developing a desktop software system stage using the latest technologies which will be relevant and easy to maintain in future development and upgrade.

Due to large-scale changes in the economy in the world and in Ukraine in particular, there has recently been a significant increase in interest in the problems of investment theory. An example is the intensification in recent years of the purchase of shares of large international companies and cryptocurrencies and, according to the rapid growth of their values. It is known that as a special case, the theory of investment considers the task of optimizing investment portfolios.

An overview of the basic principles and approaches for extracting information and processing information from web pages has been conducted. A methodology for developing a client-server system based on a tool for automation of work in Selenium web browsers based on the analyzed information about data parsing has been created. A third-party API as a user interface to simplify and speed up system development has been used. User access without downloading additional software has been enabled. Data from web pages have been received and processed.

This paper is devoted develop software for time series forecasting using Python programming language. SARIMA model was used to develop the system.

This pa­per addres­ses the prob­lem of iden­tif­ying rhe­olo­gi­cal pa­ra­me­ters of wo­od using ar­ti­fi­ci­al neu­ral net­works with pa­ral­lel le­ar­ning al­go­rithm using Python prog­ram­ming lan­gua­ge, Cha­iner fra­me­work and CU­DA techno­logy. An in­tel­li­gent system for iden­ti­fi­ca­ti­on of rhe­olo­gi­cal pa­ra­me­ters of wo­od has be­en de­ve­lo­ped. The system cre­ated con­ta­ins the most user-fri­endly in­ter­fa­ce, all the ne­ces­sary set of to­ols for au­to­ma­ti­on of the pro­cess of vis­ua­li­za­ti­on and analysis of da­ta.