A web-app which can be used to get recommendations for a series/movie, the app recommends a list of media according to list of entered choices of movies/series in your preferred language using Python and Flask for backend and HTML, CSS and JavaScript for frontend.

Building And Deploying A Netflix Recommender System On Heruko

implemented model and refined with another model which stands 3rd in the contest of 1million$ prize worth, that aims to decrease original rmse by 10 percent with efficient time-complexity.

Netflix Recommendation System using machine learning techniques specifically Singular Value Decomposition (SVD), for collaborative filtering.

Performed EDA and Dimensionality reduction on Netflix dataset to build a recommendation engine.

Recommendation System & it's types

This repository contains three AI and machine learning projects completed during the internship at Encryptix: Face Detection and Recognition System, Netflix Recommendation System, and Tic-Tac-Toe. Each project includes data preprocessing, model building, and evaluation, using OpenCV, deep learning, collaborative filtering, and game AI algorithms.

A content-based recommendation system built with Flask that suggests Netflix movies and shows based on user input. This project leverages machine learning techniques to analyze movie metadata and provide personalized recommendations.

A Content-Based Movie Recommendation System built with Machine Learning and NLP to recommend similar Netflix movies and TV shows based on genres, cast, keywords, and descriptions.