Recommender System is an information filtering tool to filter the relevant information from given information in the present era of big data. Movie Recommender System is machine learning based autonomous tool that filters the movies from big movie database like Netflix, Amazon etc. according to user preferences. Learning Rate Scheduler is optimization technique in Deep Neural Network. Learning rate is most important hyper-parameter for Deep Neural Network training. The main focus of this paper is to propose Learning Rate Scheduler for Movie Recommender System. The primary objective of this research article is to find effect of Cosine Decay Restart Learning Rate Scheduler on Movie Recommender System. Test results obtained from the Movie database show that the proposed method can bring more accurate personalized recommendations for the movie as compared to existing methods of the order of 2.224%.