#Movie-recommendation
Showing 11 of 11 repositories tagged #movie-recommendation, ranked by stars
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
Data pipeline performing ETL to AWS Redshift using Spark, orchestrated with Apache Airflow
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.
Contains code which covers various methods for recommending movies, some of the methods include matrix factorisation , deep learning based recommendation systems
Movie Recommendation System: Project using R and Machine learning
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.
NetflixGPT - OTT Platform with Movies recommendation using AI 🎦 with live Demo.
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.