Research on dynamic artificial intelligence method for deep learning of big data

Yang-Hao Wu, Peng Wang, Renchao Guo, Zhen Yang, Ling Zhou
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Abstract

In the field of artificial intelligence research, deep learning as a very active research field, mainly reflected in natural language processing, computer vision, speech recognition and other aspects. After entering the era of big data, with the continuous expansion of data scale, technological innovation of all enterprises has ushered in new opportunities and challenges, and scientific researchers have begun to use deep learning to solve the problem of big data prediction and analysis. Therefore, on the basis of understanding the research status of artificial intelligence, this paper deeply discusses the application reliability of deep learning algorithms of artificial intelligence according to the dynamic changes of deep learning of big data. The final results show that the dynamic artificial intelligence method of deep learning with big data meets the needs of practical application.
面向大数据深度学习的动态人工智能方法研究
在人工智能研究领域中,深度学习作为一个非常活跃的研究领域,主要体现在自然语言处理、计算机视觉、语音识别等方面。进入大数据时代后,随着数据规模的不断扩大,各企业的技术创新都迎来了新的机遇和挑战,科研人员也开始利用深度学习解决大数据预测分析问题。因此,本文在了解人工智能研究现状的基础上,根据大数据深度学习的动态变化,深入探讨人工智能深度学习算法的应用可靠性。最终结果表明,基于大数据的动态深度学习人工智能方法满足了实际应用的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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