38 Open Source Factorization Machines Software Projects
Free and open source factorization machines code projects including engines, APIs, generators, and tools.
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.
Tensorflow Xnn267 ⭐
4th Place Solution for Mercari Price Suggestion Competition on Kaggle using DeepFM variant.
Attentional Neural Factorization Machine40 ⭐
Attention,Factorization Machine, Deep Learning, Recommender System
some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network
AlitaNet: A click through rate (ctr) prediction deep learning Network implementation with TensorFlow, including LR, FM, AFM, Wide&Deep, DeepFM, xDeepFM, AutoInt, FiBiNet, LS-PLM, DCN, etc.
Deepcu Ijcai1918 ⭐
DeepCU: Integrating Both Common and Unique Latent Information for Multimodal Sentiment Analysis, IJCAI-19
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
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.
Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data
A library for factorization machines and polynomial networks for classification and regression in Python.
Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
Ytk Learn347 ⭐
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).
Aksnzhy Xlearn2978 ⭐
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.