Browsing by Author "Anefiyayeva D."

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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.
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    University course recommendation system
    (2022) Anefiyayeva D.
    In universities with a credit system, students are given a choice of subjects - elective courses. There is a whole list of subjects of different profiles from which they must choose themselves. This decision will affect the student’s future career, as he will choose not only the subject studied but also what he will do in the future. Understanding how difficult a choice needs to be made, and how difficult it is to choose a subject, it was decided to create a recommendation system for subjects. One of the most used applications of artificial intelligence is the recommendation engine. Since the advent of the Internet, recommender systems have become more and more common in everyday life. Recommender systems can be implemented using various machine learning methods, but this task attracts a large number of scientists from all over the world. Let’s start with how to classify k-means while comparing two different approaches. The system was developed using machine learning technology and cross-platform application development. The algorithm was based on data that was collected from various public sources. The relevance of this topic led us to create an application, two types of recommender systems: 1) Entering the subject that the student liked, the system will give him a list of subjects with similar skills 2) Entering your interests and abilities, the system gives out an item that is most suitable for your preferences