Problems of Building Machine Learning Models in Teaching Students

The article deals with the problems that arise in the process of teaching students in courses involving the development of machine learning models. The subject area is analyzed. The main problems are the low speed of building models and their verification. A solution method based on the use of fog and cloud computing environments is proposed. The conducted experimental studies showed that the time for building models decreased by 22.17 times, the speed of the teacher’s work increased by 47 %. The presented method of increasing the speed of building models can be applied in laboratory work, in the management of final qualifying works. Also, the method is applicable for building machine learning models in solving practical problems in the field of production, urban economy, in the provision of transport services, etc.