Content base movie recommendation system with sentiment analysis
It is a small project of movie recommendation system in Python and Django.
A data driven AI movie recommendation system application that leverages Machine Learning to recommend movies to users, based on their likes.
DL projects( Boltzmann-Machines, Recurrent Neural Networks, Self_Organizing_Maps)
Movie Recommendation System using correlation and pandas library in python.
This intelligent movie recommend system works on an advance machine learning model which learns the taste of a perticular user by collecting relevant data of his/her recently watched movies.
Movie recommendation software in Java
The provided code snippet performs movie recommendation based on movie metadata using the TMDB Movie Metadata dataset from Kaggle.
"Match TV" app suggests movies/TV series based on user input, using genres, cast, and creators for personalized recommendations.
Movie Recommendation System using Item-Based
Content-Based Movie Recommendation System
The Movie Recommendation System is a Python application that provides personalized movie suggestions using collaborative and content-based filtering techniques. Utilizing the MovieLens 25M dataset, it offers customizable recommendations based on user ID, movie title, and desired suggestion count, creating an engaging and tailored movie discovery.
I choose the TMDb movie data set for data analysis. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.I would like to find other intresting patterns in the dataset.
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