netflix-recommendation-system

Nexus VST Peak

Network Unlock Android Flow

Netflix Flow

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.

Nexus VST

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.

Building And Deploying A Netflix Recommender System On Heruko

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

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.

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.