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Flix

Screenshot 2024-06-07 123320

https://flix.arunnats.com/

Flix is a movie recommender app which utilizes the MovieLens database to provide personalized movie recommendations based on user preferences. The app employs a collaborative filtering technique, leveraging a correlation matrix derived from user ratings. It selects the top-rated movies and those with a substantial number of reviews to build a correlation matrix, which forms the backbone of the recommendation engine.

Machine Learning and Python

The recommendation engine's machine learning model is implemented using Python, leveraging libraries such as numPy, MathPlotLib, Seaborn, and SciKit-Learn. Python is used for the data analysis tasks, including building correlation matrices and exporting them as pkls for further processing.

Screenshot 2024-06-07 123447

Features

  • Recommendation Engine: Generates movie recommendations based on user preferences and ratings.
  • Live Search: Allows users to search for movies in real-time using a live search feature.
  • Data Visualization: Visualizes movie data using various graphs and charts to provide insights into movie ratings, genres, and other relevant information.
  • Database Integration: Utilizes MySQL for storing movie names and facilitating live querying and seamless integration with the recommendation engine.

Technologies Used

  • Frontend: React, Tailwind CSS.
  • Backend: Vite, Node, FastAPI.
  • Database: MySQL.
  • Data Analysis and Machine Learning Model: Python, numPy, MathPlotLib, Seaborn, SciKit-Learn.

Screenshot 2024-06-07 123400

How It Works

  1. Data Collection: The app retrieves movie data from the MovieLens database, including user ratings and movie information.
  2. Correlation Matrix Generation: It constructs a correlation matrix based on user ratings, focusing on highly-rated movies and those with a significant number of reviews.
  3. Recommendation Generation: Using the correlation matrix, the app generates movie recommendations tailored to each user's preferences.
  4. Live Search: Users can search for movies in real-time using the live search feature, which fetches results dynamically as the user types.
  5. Data Visualization: The app visualizes movie data using various graphs and charts, providing users with insights into movie ratings, genres, and other relevant metrics.

License

This project is licensed under the MIT License - see the LICENSE file for details.