Factorization Machine models in PyTorch
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Updated
Apr 8, 2024 - Python
Factorization Machine models in PyTorch
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
tf-recsys contains collaborative filtering (CF) model based on famous SVD and SVD++ algorithm. Both of them are implemented by tensorflow in order to utilize GPU acceleration.
A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, anomaly detection, and etc.
Using Hybrid Fuzzy logic and Genetic Algorithms to build a faster and accurate recommender system.
Built a Movie Recommendation System using AutoEncoders.It was built using MovieLens Dataset
Movie Recommendation System using the MovieLens dataset
A recommendation algorithm implemented with Biased Matrix Factorization method using tensorflow and tested over 1 million Movielens dataset with state-of-the-art validation RMSE around ~ 0.83
Movie Website built on python Django framework; Uses Content Based Predictive Model approach to predict similar movies based on the contents/genres similarities
Basic recommendation system for Movilens dataset using Keras
Neural Collaborative Filtering with MovieLens in pytorch
Bayesian Personalized Ranking in Python
This is movie recommendation system with pandas back-end. There are a few things you can do with it. Search for movie, find movie what to watch based on genre and when you have watched a movie to find other movies similar to it.
Basic Recommender System that provides Content Based Filtering or Product based Recommendations over MovieLens Movies data-set to be used with native and AWS EMR Hadoop
A recommendation algorithm using the MovieLens dataset.
Script to run and find similarities between movies from a movie lens data set using Python & Spark Clustering.
Comparison of Recommender System Algorithms on MovieLens Dataset. Experimentation with Hybrid approach combining the algorithms. Implementation of interest sequence based collaborative filtering.
Implementation of various popular Collaborative Filtering algorithms in Python.
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