Research on the application of deep learning in data mining

With the rapid development of information technology, the amount of data has exploded, and traditional data processing and analysis methods are no longer able to meet current needs. Deep learning, as a new machine learning technology, has shown great potential and application value in the field of data mining due to its powerful feature extraction capabilities and efficient processing speed. This article aims to explore the application of deep learning in data mining and analyze the challenges it faces and future development trends. This article first introduces the basic concepts, classification, and application fields of data mining, and then elaborates on the basic principles, key technologies, and advantages of deep learning. On this basis, this article focuses on analyzing the application of deep learning in key links of data mining such as data preprocessing, feature learning, pattern recognition, and anomaly detection, and verifies the effectiveness of deep learning models through experiments. In addition, this article also discusses the main challenges faced by deep learning in data mining, including computational resource requirements, model interpretability issues, and data privacy protection, and proposes corresponding solutions. Finally, this article summarizes the research findings and provides prospects for the future development of deep learning in the field of data mining. This article not only provides theoretical basis and practical guidance for the application of deep learning in data mining, but also provides new ideas and methods for researchers in related fields.