Research on Complex Data Mining Analysis and Pattern Recognition Based on Deep Learning
Jieting Lian, Taiying Chen
Abstract
This paper systematically investigates and discusses the application of deep learning in complex data mining analysis and pattern recognition. Firstly, it introduces the basic concepts of deep learning and commonly used models, including artificial neural networks, convolutional neural networks, and recurrent neural networks. Then, it elaborates on the application methods and techniques of deep learning in mining different types of complex data (such as images, text, time series, etc.), and explores the latest research progress in the field of pattern recognition. Furthermore, it analyzes the challenges faced by deep learning in practical applications, such as data scarcity and model generalization capabilities, and proposes future development trends and research directions. Finally, it summarizes the research content and significance of this paper, emphasizing the importance and application prospects of deep learning in the field of complex data mining and pattern recognition.