A MODEL FOR DETERMINING THE DIRECTIONS OF SCHOOL GRADUATES BASED ON MACHINE LEARNING ALGORITHMS (International Scientific Journal Alfraganus, 2024)
The purpose of this article is to determine the orientation of schoolchildren in terms of grades insubjects and soft skills using machine learning methods. The article examined the difficulties of constructing asigmoid function using multivariate linear regression, and also digitized grades obtained in selected subjects in thefield of student education over 10 years and their various parameters, reasons and student capabilities. . Using thesenumbers, a training data set was created. As a result, a classification of subjects studied by schoolchildren over 10 yearsand their assessments was developed. Neural network architectures, modules, the most commonly used activationfunctions in machine learning algorithms, training methods and methods for constructing linear and logistic regression,disadvantages and opportunities are analyzed. Ways to simplify the gradient descent function for multivariate linearregression by vector calculation have been studied. Because there are many variables involved in this type of linearregression, vector calculations have proven to be more convenient. Methods for parallel calculation of gradient descentprocesses using vector calculations are also considered. In particular, the addition of training data table columns,transposition of coefficients - AT, vectorized representation of a linear function, hyperparameters for gradient descent(learning rate - , number of steps) were defined.
Keywords: adding columns, transposing coefficients - AT, vectorized representations of linear functions, hyperparameters for gradient descent