There are more number of movies has been released the user gets confusion, which movie is suit for them and difficult to choose, so to become easier the recommendation system comes into play if the user search a movie it gives a accurate result with similar various suggestion . The suggestion movies are given by the recommendation system by the user search e.g., if the movie is action, love, crime, drama or by the director the similar movies will be suggested. The recommendation systems are used to recommend movies using the user previews choice. The Sentiment Analysis which helps to analyse the users sentiments, which is based on their choice.In recent year, the sentimental analysis became one of most major things for many of the recommendation systems

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The primary way to classify retinal illnesses is to conduct several medical examinations, the most important of which is a visual examination. Human error is common as a result of a poor-higher cognitive process, which is one of the major challenges in visual disease diagnosis. Automated image processing technologies are more useful for early disease diagnosis and evaluation than the digitized diagnostic imaging conventional operations are confusing and time-consuming. The aim of this paper is to create a system that detects retinal abnormalities based on images using Deep learning technique. The images are first pre-processed. The photographs are enhanced after they have been pre-processed. The images that have been pre-processed are fed into the Penta-Convolutional Neural Network (Penta-CNN). Penta-CNN is a five-layered architecture that includes two convolutions, max pooling, and three fully connected layers. The performance of Penta-CNN is evaluated using STARE(Structured Analysis of the Retina) database [14]. The model is also trained with several hyperparameters which are tweaked and assessed.