It is a blueprint to data science from the mathematics to algorithms. It is not completed.

たまに追加される論文メモ

Repository for the Honor Track of Recommender Systems Specialization from University of Minnesota on Coursera

This repository contains a simple but efficient implementation of an argument-based recommender system, which makes use of NLP techniques and a taxonomy and lexicon of connectors to extract argument graphs from the proposals and citizen debates available in the Decide Madrid e-participation platform.

This repository offers a wide range of data science and machine learning projects, interview home tasks, and comprehensive interview preparations to help both beginners and experienced practitioners master the concepts and enhance their skills.

Evaluating k-nearest neighbors and singular value decomposition techniques for collaborative filtering recommender systems

Labs of COM-308@EPFL, 2024 Spring

Provides the Jester Dataset for package recommenderlab.

By 2020, Board Game Geek featured over 36,000 board games, with 5,000 new games introduced that year alone. To manage this rapid influx and effectively connect players with the right games, the team developed a Meta-level hybrid recommendation system for the Board Game Geek platform.

Provides the Book-Crossing Dataset for the package recommenderlab.