| ITI əməkdaşlarının elmi işləri - məqalə |
| Biblioqrafik təsvir | |
| Hajirahimova , M.S. Deep learning approaches for big data analytics: opportunities, issues and research directions / M.S. Hajirahimova , A.S. Aliyeva // Восточно Европейский Научный Журнал. - 2020. - N: vol60 isuuse 8 part3. - P. 26-33. | |
| Annotasiya | |
| Over the last few years, Deep learning has begun to play an important role in analytics solutions of Big Data. Deep learning is one of the most active research fields in machine learning community. It has gained unprecedented achievements in fields such as computer vision, natural language processing and speech recognition. The ability of deep learning to extract high-level complex abstractions and data examples, especially unsupervised data from large volume data, makes it attractive a valuable tool for Big Data analytics. In this paper, discuss the challenges posed by Big Data analysis. Next, presented typical deep learning models, which are the most widely used for Big Data analysis and feature learning. Finally, have been outlined some open issues and research trends. | |
| Elektron variant | |
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