bit-guber / frontend-movie-recommender

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Frontend of Movie Recommendation System

This Project accomplish top 50 Movie suggest for user from previously liked movies with quick and efficiently as possible way.
this project fetch suggest from created API point that source here. this only frontend made by bit_guber with React + Vite + TypeScript tools.

Currently, How it Works? It follows a few steps:

• Initially Page
• Selected a Movie
• ReConfiguring Recommended Page

Home Page

There will be Top 100 Popular Movies based on reviews count each movie in MovieLens Dataset which were collected 9,734 movies over various periods of time.

this may be various from real time top movie but focus on dataset is a viral source information.

Watched and Liked Movie

Everytime a user select a movie from the list then redirect API point.

Recommended Page

this where API server response come to work, Response contains high probability movies that similar to previous Liked Movie list.

Actually response produce by The famous SVD Machine learning algorithm based on Matrix Factorization and this same used Simon Funk during the Netflix Recommended Engine Prize. also that produce efficient and more relate suggestion.