A Movie Recommendation System using KNN Algorithm
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The Movie Recommendation System is a ** Recommendation Systems ** tool designed to suggest movies based on user preferences and viewing history. It leverages the ** KNN Algorithm ** to provide personalized recommendations by analyzing patterns in user behavior and movie characteristics. The system allows users to upload datasets and generates tailored recommendations, making it a powerful tool for cinephiles and streaming platforms alike.
• KNN Algorithm Integration: Utilizes the K-Nearest Neighbors algorithm to ensure accurate and relevant recommendations.
• Customizable Recommendations: Users can upload their own datasets to train the system for personalized suggestions.
• User-Friendly Interface: Easy-to-use platform for uploading datasets and viewing recommendations.
• Real-Time Processing: Generates recommendations quickly, even with large datasets.
• Diverse Movie Suggestions: Covers a wide range of genres and preferences to cater to all types of audiences.
What algorithm does the Movie Recommendation System use?
The system uses the KNN Algorithm (K-Nearest Neighbors) to generate recommendations based on user preferences and movie attributes.
Can I upload my own dataset?
Yes, the system allows users to upload their own datasets for training and generating personalized recommendations.
How long does it take to generate recommendations?
The system processes datasets in real-time, providing recommendations quickly even with large datasets.