SUN’IY INTELLEKT ASOSIDA AXBOROT TIZIMLARIDA MA’LUMOTLARNI QAYTA ISHLASH SAMARADORLIGINI OSHIRISH

Abstract

This article investigates the use of artificial intelligence and machine learning technologies to improve the efficiency of processing large volumes of data in information systems. The rapid growth of data volumes in modern information systems is increasing the requirements for data collection, cleaning, classification, analysis, and forecasting processes. Although traditional deterministic algorithms provide high efficiency for certain types of tasks, their capabilities may be limited when dealing with large, complex, and dynamically changing datasets. The study analyzes traditional and artificial intelligence-based approaches to data processing and proposes a model for integrating AI components into the data flow of an information system. In addition, the stages of data preprocessing, feature extraction, classification, and evaluation of the obtained results are considered. An example of implementing a machine learning model in the Python programming language is provided. To evaluate efficiency, such indicators as execution time, accuracy, memory consumption, and the F1-score are proposed. The results of the study demonstrate that the proper integration of artificial intelligence technologies into information systems can automate data processing procedures and improve the quality of decision-making.