ludovikcoba

recoxplainer

rrecsys

rrecsys: Environment for Assessing Recommender Systems

iea2017

NMF

2018_WIMS_code

bootstrap

The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

CBC

coding_problems

DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

expl_MF

IJAIT

moviegeek

A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.

nlp_paper_summaries

✍️ A carefully curated list of NLP paper summaries

pyreclab

pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, GRIMA Lab and SocVis Lab.

rankBasedConjoint

reco-gym

Code for reco-gym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising

recoxplainer.github.io

rrecsys-site

word2vec