This project implements a robust recommender system for book recommendations, leveraging ensemble methods, user-specific strategies, XGBoost, and extensive data preprocessing to achieve high performance in the Recommender System 2023 Challenge hosted by Kaggle for students of Politecnico di Milano's Recommender Systems course.
ecommerce recommendation
initial fork from
Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.
Intern project to implement recommender demos for implicit feedback transaction data.
Tools for development of recommendation systems in Python.
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.
Implementation of various collaborative filtering methods for recommender systems with implicit feedback
This project is a recommendation system built with implicit ALS algorithm using Netflix UK's watch history data. It provides personalized movie recommendations and exposes a FastAPI API route for easy integration.
Neural collaborative filtering (NCF) method is used for Microsoft MIND news recommendation dataset.
使用矩阵分解算法处理隐式反馈数据，并进行Top-N推荐。The matrix factorization algorithm is used to process the implicit feedback data and make top-N recommendation.
A Julia implementation of three different recommender systems based on the concept of Neural Collaborative Filtering.
Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi
Benchmarking different implementations of weighted-ALS matrix factorization
Recommender system weighted regularized matrix factorization in python
Reranks and expands Solr query returns using clickstream data
Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation, SIGIR 2021
Recommender System toolkit
A hybrid recommender system for suggesting CDN (content delivery network) providers to various websites
A set of matrix factorization techniques to provide recommendations for implicit feedback datasets.
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