26 Open source projects that are alternatives of or similar to spark-fm

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#nowplaying-RS: Music Recommendation using Factorization Machines

Building recommender systems in Julia

零售电商客户流失模型，基于tensorflow，xgboost4j-spark，spark-ml实现LR，FM，GBDT，RF，进行模型效果对比，离线/在线部署方式总结

A library for factorization machines and polynomial networks for classification and regression in Python.

DeepTables: Deep-learning Toolkit for Tabular data

Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.

KDD17_FMG

🌊 FluRS: A Python library for streaming recommendation algorithms

Fwumious Wabbit, fast on-line machine learning toolkit written in Rust

Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data

some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

Attention,Factorization Machine, Deep Learning, Recommender System

fastFM: A Library for Factorization Machines

TensorFlow implementation of an arbitrary order Factorization Machine

Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communication.

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

Factorization Machine models in PyTorch

TenforFlow Implementation of Neural Factorization Machine

Some deep learning based recsys for open learning.

TensorFlow Implementation of Attentional Factorization Machine

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Tensorflow implementation of DeepFM variant that won 4th Place in Mercari Price Suggestion Challenge on Kaggle.