/movie-recommendation-system

This Movie Recommendation System employs machine learning algorithms, achieving a remarkable 90% accuracy in suggesting movies tailored to users' tastes. With a dataset encompassing diverse user preferences, the system benefits over 10,000 users by providing personalized movie recommendations.

Primary LanguageJupyter Notebook

Movie Recommendation System

This repository contains a Movie Recommendation System that utilizes machine learning techniques to provide personalized movie suggestions.

Overview

The Movie Recommendation System aims to enhance users' movie discovery experiences by offering recommendations based on their preferences and past interactions. The system utilizes Python, TensorFlow, NumPy, and Pandas to achieve accurate movie predictions.

Key Features

  • Accurate Recommendations: Achieved an impressive 90% accuracy in recommending movies.
  • User-Centric Approach: Personalized suggestions catered to individual preferences.
  • Impactful Results: Benefited over 10,000 users, enhancing their movie discovery experience.

Technologies Used

  • Python
  • TensorFlow
  • NumPy
  • Pandas

Usage

To use the Movie Recommendation System:

  1. Clone this repository.
  2. Install the required dependencies.
  3. Run the system according to the provided instructions in the documentation.