The trend of the Internet makes the presentation of the right content for the right user inevitable. To this end, recommendation systems are used in areas such as music, books, movies, travel planning, e-commerce, education, and more. One of the most popular recommendation systems in the world is Netflix, which generated record profits during quarantine in the first quartile of 2020. The systematic approach of recommendations is based on the history of user selections, likes and reviews, each of which is interpreted to predict future user selections. This article provides a meaningful analysis of various recommendation systems, such as content-based, collaborative filtering and popularity. We reviewed 7 articles published from 2005 to 2019 to discuss issues related to existing models. The purpose of this article is to compare machine learning algorithms in the Surprise library for a recommendation system. Recommendation system has been implemented and quality has been evaluated using the MAE and RMSE metrics.

The trend of the Internet makes the presentation of the right content for the right user inevitable. To this end, recommendation systems are used in areas such as music, books, movies, travel planning, e-commerce, education, and more. One of the most popular recommendation systems in the world is Netflix, which generated record profits during quarantine in the first quartile of 2020. The systematic approach of recommendations is based on the history of user selections, likes and reviews, each of which is interpreted to predict future user selections. This article provides a meaningful analysis of various recommendation systems, such as content-based, collaborative filtering and popularity. We reviewed 7 articles published from 2005 to 2019 to discuss issues related to existing models. The purpose of this article is to compare machine learning algorithms in the Surprise library for a recommendation system. Recommendation system has been implemented and quality has been evaluated using the MAE and RMSE metrics.

In our research work, we study transport card security issues. One of the questions of our study is its relevance in the world and particular in Kazakhstan. Therefore, in this work, we conducted research on the market of transport cards in the world and Kazakhstan. As part of the study, we searched for answers to the following questions: what technologies are used to accept payment by transport cards, in which countries the electronic ticketing system has been introduced, in which cities of Kazakhstan have electronic ticketing systems been implemented, what technologies are used in Kazakhstan. As a result, we showed that the popularity of using NFC payment in the world and in Kazakhstan is growing. We also analyzed the existing electronic ticketing systems in Kazakhstan, made a comparative analysis and got a comparative table.