This website applies a recommendation system and continuous learning.
Introducción al Aprendizaje No Supervisado en Español
Recommending movies to user using various Colaborative Filtering and Content Based Filtering.
Research about Massive Data Processing Techniques in Data Science
Tool for simplifying to perform experiments with collaborative filtering models
A hybrid movie recommendation system developed with data from The Movie Database (TMDb)
This Repo contains The Implementation of Content-Based Recommended System and Collaborative Filtering Recommended System for movies dataset in python.
Sistema de Recomendacion de la plataforma Steam desarrollado
✨🎬 Explore seu Próximo Filme Favorito! Um sistema de recomendação colaborativa que personaliza sua experiência de entretenimento. 🍿✨
The is a course project, a within-class kaggle competition targeting to recommend the courses to the potential buyer.
Recommender System Project This repository contains the implementation of various recommender system algorithms, including KNN, SVM, Decision Tree, and Matrix Factorization. The primary focus is on Matrix Factorization to provide personalized movie recommendations using the MovieLens dataset.
This project builds a scalable recommendation system inspired by Netflix, leveraging collaborative filtering and deep learning techniques to predict user preferences. It focuses on large-scale data processing, model training, and performance evaluation for personalized content recommendations.
Demos of various data science projects I completed - August 2023 to present. Mostly Module Assignments from MIT Course. Will add personal projects in the future here as well.
Backbones for Ranking and RecSys tasks
Recommendation Systems project from ML and BD Master Degree from UPM. Collaborative and content-based filtering competitions.
A new approach in designing and developing a collaborative-interactive movie recommender system based on user ratings
Bitcoin Core + StatsD integration Google Colab
Sore - Spotify Recomendation
Add a description, image, and links to the colaborative-filtering topic page so that developers can more easily learn about it.
To associate your repository with the colaborative-filtering topic, visit your repo's landing page and select "manage topics."