This article explores the current trends in modern data mining, emphasizing its growing automation, complexity, and user-friendliness. Key developments such as Automated Machine Learning (AutoML), Deep Learning, Explainable AI (XAI), Graph-Based Analysis, Stream Data Processing, Federated Learning, and Quantum Computing are reshaping how data is collected, processed, and interpreted. These technologies enable more efficient, transparent, and privacy-preserving data analysis across various domains, including healthcare, finance, and social networks
This article explores the current trends in modern data mining, emphasizing its growing automation, complexity, and user-friendliness. Key developments such as Automated Machine Learning (AutoML), Deep Learning, Explainable AI (XAI), Graph-Based Analysis, Stream Data Processing, Federated Learning, and Quantum Computing are reshaping how data is collected, processed, and interpreted. These technologies enable more efficient, transparent, and privacy-preserving data analysis across various domains, including healthcare, finance, and social networks
№ | Muallifning F.I.Sh. | Lavozimi | Tashkilot nomi |
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1 | Aimbetova G.N. | Senior lecturer | Nukus State Technical University |
2 | Bekniyazova N.D. | Assistant | Nukus State Technical University |
3 | Izemetov S.B. | Assistant | Nukus State Technical University |
№ | Havola nomi |
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1 | 1.Radford, A. (2021). "Learning Transferable Visual Models From Natural Language Supervision." 2.Brown, T.(2020). "Language Models are Few-Shot Learners." 3.Luckin, R. (2018). "Machine Learning and Human Intelligence: The Future of Education."4.Aimbetoba G.N., АхunovF., Li А. Features of developing a crm system for medical centers using mysql, php and javascript technologies// Central asian journal of mathematical theory and computer sciences 2021год31.01. |