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Research on Big Data Analysis and Prediction System Based on Deep Learning

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DOI: 10.23977/autml.2023.040107 | Downloads: 422 | Views: 28647

Author(s)

Ziwei Guo 1

Affiliation(s)

1 Dickinson College, Carlisle, Pennsylvania, USA

Corresponding Author

Ziwei Guo

ABSTRACT

Along with the rapid development of information and communication technology, the amount of global data has shown explosive growth. How to effectively analyze the huge amount of complex data, dig to realize the potential value in it and use it reasonably is one of the important topics at present. The booming development of deep learning has led to an increasing need for its use in various industries. However, the threshold of using deep learning is relatively high for general industry users, which requires a lot of time cost for learning to use and writing complex underlying models, as well as a lot of hardware cost for building deep learning frameworks such as computing servers. Based on the above-mentioned research background and current situation, this paper designs and implements a big data analysis and prediction system based on deep learning, aiming to support the use of deep learning and reduce the cost and operational complexity of users.

KEYWORDS

Big data; deep learning; prediction system

CITE THIS PAPER

Ziwei Guo, Research on Big Data Analysis and Prediction System Based on Deep Learning. Automation and Machine Learning (2023) Vol. 4: 47-51. DOI: http://dx.doi.org/10.23977/autml.2023.040107.

REFERENCES

[1] Ning Y. Research on the Application of Big Data Technology in Network Security Analysis[C]. Journal of Physics: Conference Series. IOP Publishing, 2021, 1955(1): 012015.
[2] Zhang Junyang, Wang Huili, Guo Yang, et al. A review of research related to deep learning [J]. Computer Application Research, 2018, 7:1-12.
[3] He Qing, Zhuang Fuzeng, Zeng Li, et al. PDMiner: a parallel distributed data mining tool platform based on cloud computing [J]. Chinese Science: Information Science, 2014, 44:871-885.
[4] Wang Yueqing, Dou Yong, Lu Qi, et al. DLPF: A parallel deep learning programming framework based on heterogeneous architectures [J]. Computer Research and Development, 2016, 53(6):1202-1210.
[5] Zou Y., Jin X., Li Y., et al. Mariana: Tencent deep learning platform and its applications [J]. Proceedings of the VLDB Endowment, 2014, 7(13): 1772-1777.

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