About Dataset The "Movie Recommendation System Prediction Dataset" is a comprehensive collection of movie information that serves as a valuable resource for building and testing movie recommendation algorithms. With a wide range of data including movie titles, release years, and unique item IDs, this dataset offers a rich source of information for researchers and developers seeking to create accurate and effective movie recommendation systems.
The dataset includes information about 1,682 movies from different genres and eras, allowing for a diverse and representative set of films to be included in your recommendation system. Each entry consists of an item ID and the title of the movie, making it easy to establish connections between different parts of your recommendation algorithm.
With this dataset, you can perform various data analysis and machine learning tasks, such as collaborative filtering, content-based recommendation, and hybrid recommendation system development. Whether you are a data scientist, machine learning enthusiast, or a developer working on a movie-related project, this dataset will prove to be a valuable asset in creating accurate and efficient movie recommendation systems.
From classic films like "The Godfather" and "Casablanca" to modern favorites like "Titanic" and "Pulp Fiction," this dataset covers a wide spectrum of cinematic experiences. By leveraging the data in this dataset, you can provide users with personalized movie recommendations based on their preferences, improving the overall user experience and engagement on your movie-related platform.
Link where you can find all the information: https://www.kaggle.com/datasets/muhammadbinimran/movie-recommendation-system-prediction-dataset/data?select=u.data