Research on intelligent upgrade strategy of digital platform based on machine learning

Digital platform has become one of the key factors for enterprises to succeed in today's competitive business environment. However, in order to maintain competitiveness and continuously meet the needs of users, the digital platform must be continuously upgraded and intelligent. This paper discusses the intelligent upgrade strategy based on machine learning (ML), aiming at improving the performance, user experience and business value of the digital platform. Firstly, the paper introduces the architecture of digital resource service platform, including data analysis, personalized recommendation, automatic process optimization and so on. The application of ML technology enables the digital platform to better understand user behavior, optimize resource allocation and provide more attractive functions. Next, this paper introduces a series of intelligent upgrade strategies, including key steps such as data collection and analysis, model development and training, deployment and monitoring. These strategies aim to ensure the reliability, accuracy and expansibility of ML model, thus improving the intelligence level of digital platform. The intelligent upgrade of digital platform is necessary to meet the changing market demand and user expectations. By adopting ML technology and following effective upgrading strategies, enterprises can make better use of data assets, improve operational efficiency, increase competitiveness and achieve sustainable success.