University course recommendation system
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Date
2022
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Abstract
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
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Keywords
ml, k-means, courses, universities, recommendation system