There are 8 repositories under movie-recommendation topic.
An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
The Movie Database for all language movies
Basic Movie Recommendation Web Application using user-item collaborative filtering.
🍃 Recommender System in JavaScript for the MovieLens Database
Pick your next movie using Next.js 13
Data pipeline performing ETL to AWS Redshift using Spark, orchestrated with Apache Airflow
The purpose of our research is to study reinforcement learning approaches to building a movie recommender system. We formulate the problem of interactive recommendation as a contextual multi-armed bandit.
Movie Recommendation System with Complete End-to-End Pipeline, Model Intregration & Web Application Hosted. It will also help you build similar projects.
Content based movie recommendation system with sentiment analysis
Python操作Neo4j数据库,知识图谱,根据相似度计算的一个电影推荐的Demo
Movie Recommender System with Django.
使用MovieLens数据集实现了基于Auto Encoder(AE), Variational Auto Encoder(VAE), BERT的深度学习电影推荐系统
Theatherflix Extension is a browser extension that provides personalized movie and series recommendations to users. Using The Movie Database (TMDb) API, the extension fetches popular movie data and displays customized suggestions based on user preferences.
Contains code which covers various methods for recommending movies, some of the methods include matrix factorisation , deep learning based recommendation systems
Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.
The Indian Movie Database - supports content-based and collaborative filtering techniques
一个简单的电影推荐网站,基于爬取的豆瓣电影数据和协同过滤算法,使用Django框架搭建。demo曾获全国应用统计研究生案例大赛二等奖。
🎥 Movie Recommender AI System
Movie Recommendation System: Project using R and Machine learning
NetflixGPT - OTT Platform with Movies recommendation using AI 🎦 with live Demo.
This is a Machine Learning project to create a "Movie Recommender System" and predict user ratings for movies using cosine similarity.
Designed a movie recommendation system using content-based, collaborative filtering based, SVD and popularity based approach.
Code for paper: Learning to Build User-tag Profile in Recommendation System
Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.
Movie watchlist and journal app built with Vue 3 and Fauna DB. All future development of this project has moved to Codeberg.
Movie recommender system with Collaborative Filtering using PySpark
It is a movie recommender web application which is developed using the Python.
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