Using Machine Learning Techniques to Predict a Possible Rating of Mobile Applications

The thesis is devoted to the research of a relevant topic of forecasting the rating of mobile applications. The aim of this work is to conduct a comparative analysis of machine learning techniques to predict the rating of mobile applications. The first chapter describes the current state of the field of mobile application marketing and provides an overview of machine learning techniques. In the second chapter, corresponding technological tools are studied; The description of various metrics for evaluation the quality of models is given. The third chapter presents the results of an experimental study of the selected machine learning techniques on a data set evaluated by the quality metrics. The results of the work are of interest both to researchers engaged in theoretical developments in the field of machine learning techniques, and to practitioners working in the field of digital marketing.