The article presents the study of the use of digital technologies for flipped learning implementation. In this context, the use of the virtual learning environment has been analyzed. The assessment of the efficiency of flipped learning implementation based on this environment and the process of defining the ways of improving the components of the scientific-methodological system of flipped learning was carried out using the technologies of machine learning. The innovative and personalized nature of flipped learning implemented with the use of the virtual learning environment is a methodological condition for increasing the students’ interest in learning, activating their study process, revealing their cognitive and personal potentials as well as developing digital competences, independence and individuality etc. The authors emphasize that the use of flipped learning based on digital technologies requires thorough development of the virtual learning environment, a detailed selection of the study content and its adaptation to the concrete groups of students. By stating this we mean the search for more effective and systemic ways of achieving learning objectives: the methods of problem-based learning, flipped learning; the selection of digital tools for presenting lecture materials, development of supplementary tasks; correction of the theoretical materials and the tasks on the basis of the study results and achievements of the students; motivating students to work with the study materials on their own etc. Machine learning was used to group the students by clustering the results of their educational achievements. Based on these data, the personalized learning vector, characteristic of a specific group of students, was determined.