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In recent years, deep learning techniques have gained significant attention in the field of recommender systems. This paper explores the application of deep features for movie recommendation on the Movies4U dataset. We investigate the effectiveness of various deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in extracting meaningful features from movie data. Our experimental results demonstrate that deep features can significantly improve the performance of movie recommendation systems. Even if you ignore the legal issues, the