DeepCU-IJCAI19

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.

Factorization Machine models in PyTorch

TensorFlow implementation of an arbitrary order Factorization Machine

Some deep learning based recsys for open learning.

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 tracker based on joint probabilistic data association filtering.

A highly-modularized and recommendation-efficient recommendation library based on PyTorch.

scikit-fusion: Data fusion via collective latent factor models

A parallel implementation of factorization machines based on Spark

This repo includes some graph-based CTR prediction models and other representative baselines.