🎥 Uses content based filtering and weighted average

Recommend movies to users based on their previous movie ratings Based on previous activities or explicit feedback, content-based filtering recommends other items similar to what the user likes.

AFFY (A Film For You) is a Content-Based recommender system for movies

This is Content based music recommendation system. I have used both audio features and lyrics (text based) features for recommending most similar songs to a given query song.

Movie Recommender

Movie Recommendation Web+Desktop App working on both Content+Collaborative-Based filtering

content-based movie recommender. The recommender system takes input movies and recommends movies from the top 250 rated movies according to IMDB. Recommendations are generated according to Genre, Directors, Main Actors, and Plot.

The learning material and projects for the ML algorithms in supervised and unsupervised methods such as Regression, Classification, Clustering and recommender Systems.

Recommender Engine to Suggest relevant content to each user

Popularity based, Content based recommender & Colaborative Filtering systems

Building a recommendation system using both collaborative filtering and content-based filtering

Some basic recommendation systems for various books

Movie Recommender System Machine Learning Model

Movie recommender system

using machine learning content based algorithm to build book recommendation system

The recommendation system for BetterMart (an ecommerce website developed by me) is a Python implementation that leverages cosine similarity to provide personalized product recommendations to users. This system analyzes the characteristics and features of products to identify similarities and suggest items that align with a user's preferences.

Movie Recommendation System using Popularity, Content and Collaborative Based Recommendation methods