🔮Trying to find the best movie to watch on Netflix can be a daunting. Case Study for Recommendation System of movies in Netflix.🔧

This repository contains collaborative filtering recommender system build in Python with surprise package to predict book ratings in Book-Crossing dataset.

Recommendation Systems tutorial

Movie recommendation system to find common movie interests among a group of people.

This repo contains my practice and template code for all kinds of recommender systems using SupriseLib. More complex and hybrid Recommender Systems can build on top of these template codes.

Deployed Product Recommendation Model using collaborative filtering.

Use the Scikit-Network for PageRank algorithms including Topic-specific PR and improve the performance of various recommendation-systems using Surprise library

Build a movies recommendation system clone using Movielens dataset to construct recommendation system such as Simple recommender, Content based recommender (based on movie description and metadata) , Collaborative-Filtering based recommender , and a Hybrid recommender system.

To recommend the next 10 movies to the user using the Prized Dataset provided by Netflix - over the span of 10 days for Capstone Project.

A book recommendation system using model based collabritive filtering. It is based on SVD machine learning model. It generate top 10 recommendation of books.Here i used surprise library.

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Simple Recommender Systems

Système de recommandation

Evaluating and comparing recommender system models using MovieLens-Ratings dataset

This project focuses on predicting Loan Defaults using Supervised Learning, Segmenting Customers with Unsupervised Learning, and Recommending Bank Products through a Recommendation Engine.

Predict user rating for a netflix movie.

A case study of the Netflix Prize solution where, given anonymous data of users and the ratings given to movies, the objective to provide recommendations to users for movies which they would like, based on their past activity and taste.

Did you ever wonder how the recommendations on Netflix work? Find out in this project, where I build three basic movie recommenders and implement them in a streamlit App.

A Book Recommender System: Collaborative Filtering using Surprise (k-NN Baseline model)