研究了基于深度神经网络的电影风格迁移方法，以及大数据和机器学习在其中的作用。首先介绍了电影风格迁移的基本概念和现有研究，然后分析了人工智能如何实现电影风格的迁移，包括使用的算法、技术和方法，以及评估的指标和标准。接着，探讨了大数据和机器学习如何提高电影风格迁移的效率和质量，拓展其范围和可能性，以及创造新的电影风格和表达方式。最后，批判性地分析了基于大数据和机器学习的AI导演电影风格迁移方法所面临的伦理、技术和评价问题，并提出了一些可能的解决方案和改进方向。

This paper studied the movie style transfer methods based on deep neural networks, and the role of big data and machine learning in them. First, it introduced the basic concept and existing research of movie style transfer, then analyzes how artificial intelligence achieves movie style transfer, including the algorithms, techniques and methods used, and the indicators and standards for evaluation. Next, it discussed how big data and machine learning improve the efficiency and quality of movie style transfer, expand its scope and possibility, and create new movie styles and expression ways. Finally, this paper critically analyzed the ethical, technical and evaluation problems faced by the AI director movie style transfer methods based on big data and machine learning, and proposes some possible solutions and improvement directions.