Browsing by Author "Anefiyayev N."

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    Application for predicting the business orientation based on analysis of user desires
    (2023) Anefiyayev N.
    In today’s competitive business landscape, understanding customer desires and preferences is crucial for the success of any organization. Customer churn is a significant problem for companies and describes moving out of customers to competitors. Predicting such behavior in advance offers companies valuable insights, empowering them to take measures to retain their customer base and potentially d it. One key decision informed by data analysis involves identifying the development. Machine learning algorithms can data and predict business direction. This helps expand the most promising areas for business to be leveraged to analyze customer organizations, make data-driven decisions and tailor their products, services, and marketing strategies to meet customers expectations. The thesis work describes studies using their feedback, and analyzed parte for the company. To solve the problem, hms from different areas were used to how customer preferences and transactions to predict income several stages and machine learning algorithm ect for further use- Neural networks showed the best result in comparison and self business and linear regression to find out a profit. determining the direction. After that, a website and a motion of the company was visualized, and a page page where the saved model was used to predict a new partner and his income.
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    DESIGNING A RECOMMENDATION SYSTEM FOR SPECIALIZED COURSES FOR THE UNIVERSITY
    (СДУ хабаршысы - 2021, 2021) Anefiyayev N. ; Anefiyayeva D. ; Talasbek A.
    Abstract. Each university has compulsory subjects and there are subjects that the student must choose for themselves. This choice affects the further path of the student because he chooses not only the subject that he will study but also what he will work within the near future. I know from myself how difficult it is to choose a subject yourself. The recommendation engine is one of the most popular artificial intelligence applications, attracting many researchers from all over the world. From the moment we switched to the Internet, the recommendation system has become widely used in our daily life, even when we do not notice it. Many machine learning techniques can be used to implement a recommendation system, but in this work, we consider the KNN method for classification.
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    PREDICTION OF THE BUSINESS ORIENTATION BASED ON ANALYSIS OF USER DESIRES
    (СДУ хабаршысы - 2023, 2023) Anefiyayev N.; Anefiyayeva D.
    Abstract. Business is a well-established system aimed at making money and an activity that not everyone can succeed in. Business should work like clockwork that always works well with the most important - data. Only on the basis of data analysis can we make informed and rational decisions about where the business should develop, its methods became common in business when technologies for collecting and processing data developed. One of the main decisions that can be taken on the basis of data processing is to predict in which area it is better to develop a business. This paper aims to build a correct understanding of what customers are interested in based on feedback from customers. Improved machine learning solves this problem and algorithms like decision trees, neural networks, and regression are used to analyze issues and choose the best option - a foundation for the future strategy of the company.