Analysis of machine learning methods to improve efficiency of big data processing in Industry 4.0

Abstract

The article considers the basic methods of machine learning applied by individual entrepreneurs within the framework of transition to digital production to improve the efficiency of data processing, classification of existing and would-be customers and their subsequent work with them. The main attention is paid to the problem of increasing the effectiveness of methods of machine learning applied for solving the current questions. Areas of application of technology are shown. The peculiarities of machine learning are briefly analyzed. The main features and prospects of the development of Machine Learning services are shown on the basis of the concept of a step-by-step combination of the methods under consideration. One of the main algorithms for working with data is analyzed; its main features, scope and procedure are described. Recommendations are given for the further use of machine learning algorithms. The role of machine learning in the development of modern science and industry is analyzed, the main tendencies of the industry development are determined, and the practical application of big data is shown. As part of the transition to Industry 4.0, the main areas of application of machine learning, big data, Artificial Intelligence and their relations with the corresponding fields of science and production are described. The article also offers a review of the application of Artificial Intelligence and machine learning in particular in the context of the transition to digitalization and the issues of individual entrepreneurship.