Design of artificial intelligence cultural creative industry based on machine learning

Abstract

Abstract At present, social production and people's lifestyle have been revolutionized and globally affected by the rapid development of artificial intelligence technology. This technology has been reasonably applied in many fields, such as medical treatment, economy, transportation and manufacturing, so it has been unanimously recognized and supported by the market, society and the government. At the same time, artificial intelligence is more and more applied to the field of cultural industry, which brings a new development model of cultural design creative industry and promotes its production and management reform. Based on this point, this paper focuses on the practical problems in the process of small sample single label classification of cultural and creative product images, comprehensively establishes the mainstream machine learning model, and classifies DPM data with mechanical transfer learning algorithm. From the experimental data, the prediction accuracy of the resnet50 model is 87%. Not only that, this paper also proposes a multi feature algorithm by integrating machine learning and deep learning technology, in order to solve the problem of differences between large and small types of cultural and creative products. The algorithm can combine convolution calculation and point combination for learning, so as to further improve the accuracy. Finally, it can realize that the accuracy is 5% higher than DPM data set, which is conducive to the development of cultural and creative industries. Through the in-depth analysis of artificial intelligence, it is found that the technical level of artificial intelligence needs to be improved at this stage, and there are limitations in its application; Artificial intelligence laws and regulations are imperfect and information protection is misplaced; Artificial intelligence technology is easy to be overused, which affects the healthy development of cultural industry and leads to public opinion. This paper applies machine learning and artificial skill technology to the field of cultural and creative design, so as to promote the development of cultural and creative industry.