Pick Me A Flick: A content filtering based Movie Recommendation Engine .

Movie Recommender System project, This web application offers the functionality of suggesting a set of five movies based on the user’s selection.

A content-based movie recommendation system that recommends movies based on user preferences using cosine similarity.

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 Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

This project is a movie recommender engine written using Python and the Scikit-Surprise libraries to generate better movie recommendations by utilizing temporal user interactiondata.

Movie Recommendation System based on machine learning concepts

Rate movies and get recommendations.

This is a basic ML app which recommends movies based on your entered movie name. Deployed using Flask API

I made a Movie recommendation Engine using Content Based Filtering, Collaborative filtering. In content Based Filtering I done Preprocessing of data, used Average-weighted-rating technique, Statistical Approach, Vectorization, Cosine Similarity. While in Collaborative I done some Preprocessing of data, Make Pivot table, Vectorization, Correlatio…

An intuitive movie recommendation system leveraging genre similarity with TF-IDF and cosine similarity for a personalized film discovery experience.

Project on preference learning - ENSAE ParisTech

A content-based recommender system that recommends movies similar to the movie the user likes.

movie recommender

A movie recommender that recommends movies using the K Nearest Neighbours algorithm from a list of ~5000 movies

Movie Recommender System with Django.

This is a Simple Movie Recommender developed and hosted at codesandbox.

Basic Movie Recommendation Web Application using user-item collaborative filtering.

Sistem rekomendasi yang dibangun merupakan aplikasi berbasis web yang menggunakan bahasa pemrograman Python, HTML, CSS, Javascripts, Framework Bootstrap dan Django. DBMS yang digunakan adalah Neo4J berbasis graph database dengan menggunakan query Cypher. Data yang digunakan yaitu dataset movie recommender. Sistem ini memiliki 4 menu utama yaitu …