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This final qualifying work presents the development of a comprehensive PR campaign aimed at promoting Azimut Hotel Saint Petersburg in the digital environment. The study emphasizes the importance of client communication through modern digital tools, particularly in the highly competitive hospitality market.
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РазÑабоÑка коÑпоÑаÑивного ÑайÑа
2019This graduate work of the bachelor describes the creation of a corporate website for the use of employees of the company, to perform those or other office tasks, as well as maintain the logistics of on-site engineers. The Internet in our time has become one of the most important resources in the work of each office.
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ТÑговÑй мобилÑнÑй ÑобоÑ
ЦелÑÑ ÑабоÑÑ ÑвлÑеÑÑÑ ÑазÑабоÑка ÑÑгового мобилÑного ÑобоÑа, пÑедназнаÑенного Ð´Ð»Ñ ÐºÐ¾Ð»Ð»ÐµÐºÑивного пеÑÐµÐ´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð³ÑÑзовой плаÑÑоÑмÑ, Ñ ÑÑеÑом оÑÑÑÑÑÑÐ²Ð¸Ñ Ð½Ð°ÐºÐ»Ð¾Ð½Ð° коÑпÑÑа и пÑоÑкалÑзÑÐ²Ð°Ð½Ð¸Ñ ÐºÐ¾Ð»ÑÑ,openaire +1 more source
2016
In this final qualification work the teoretiko-legal basis of institute of liquidation and bankruptcy of the legal entity are covered. The extensive complex of the legal issues connected with protection of the rights of creditors in case of liquidation of the legal entity from the point of view of the modern Russian legislation is considered.
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In this final qualification work the teoretiko-legal basis of institute of liquidation and bankruptcy of the legal entity are covered. The extensive complex of the legal issues connected with protection of the rights of creditors in case of liquidation of the legal entity from the point of view of the modern Russian legislation is considered.
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ХимиÑ. СбоÑник Ð·Ð°Ð´Ð°Ñ Ð¸ ÑпÑажнений
РпоÑобии пÑедÑÑÐ°Ð²Ð»ÐµÐ½Ñ Ð·Ð°Ð´Ð°Ñи и ÑпÑÐ°Ð¶Ð½ÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑекÑÑего конÑÑÐ¾Ð»Ñ Ð·Ð½Ð°Ð½Ð¸Ð¹ по диÑÑиплине «ХимиÑ» Ð´Ð»Ñ ÑÑÑденÑов Ð½ÐµÑ Ð¸Ð¼Ð¸ÑеÑÐºÐ¸Ñ ÑпеÑиалÑноÑÑей вÑÑÑÐ¸Ñ ÑÑебнÑÑ Ð·Ð°Ð²ÐµÐ´ÐµÐ½Ð¸Ð¹, пÑÐ¾Ñ Ð¾Ð´ÑÑÐ¸Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¿Ð¾ Ð½Ð°Ð¿Ñ ...openaire +1 more source
The purpose of the work is to develop a prototype of the prototype of the recommender system of the choice of goods using filtering algorithms. The following tasks were solved: â machine learning methods in recommender systems were analyzed; â existing analogs of the recommendation system under development were studied; â technologies and tools ...
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