Data imputation with collaborative filtering and latent factor models for wind farms time series data

A movie recommend app using React-native and integrated AI recommender system: LFCF-DL and Content-Based Filtering.

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

A collaborative-filter-based music recommender machine

Recommendation Systems with mathematical modelling

Correction of batch effects in DNA methylation data

Correction of batch effects with BEclear as a command line tool

implemented model and refined with another model which stands 3rd in the contest of 1million$ prize worth, that aims to decrease original rmse by 10 percent with efficient time-complexity.

Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).

Practicing traditional filtering approaches for recommender systems on Kaggle expedia-hotel-recommendations problem | University Project

Chaos - a first of its kind framework for researching Reciprocal Recommender Systems (RRS).

Programas en proceso de desarrollo de mi tesis basada en sistemas de recomendacion, collaborative filtering por ahora, falta agregar content based. De collaborative filtering tanto memory based como model based.

Engine to recommend the best TV shows for users, using Collaborative Filtering and Latent Factor Model

Recommender system with Netflix database using matrix factorization

An implementation for our paper: Time sensitivity-based popularity prediction for online promotion on Twitter (Information Sciences, 2020). This is an extended Latent Factor Model that can predict popularity values of tweets on Twitter when they are published at various times. The data includes Twitter user profiles and tweet information (tweetI…

Implementing different approaches for recommendation systems

Implementation of various recommender systems, for course CS F469 Information Retrieval

Recommender System to predict movie ratings