Sparse Data

DSSTNE - Amazon's library for building Deep Learning modelsC++

An open-source library for training and deploying deep learning recommendation models with sparse data at scale using multi-GPU support.

xLearnC++

A high-performance, easy-to-use, and scalable machine learning package for linear models, factorization machines, and field-aware factorization machines.

TileDBC++

An embeddable C++ storage engine for dense and sparse multi-dimensional arrays, dataframes, and key-value stores.

vectorflowD

A minimalist neural network library optimized for sparse data and single-machine environments.

fastFMPython

A Python library implementing Factorization Machines with a scikit-learn compatible API for regression, classification, and ranking tasks.

tffmJupyter Notebook

TensorFlow implementation of arbitrary order (≥2) Factorization Machines for classification and regression tasks.

somocluC

A massively parallel library for training self-organizing maps on multicore CPUs, GPUs, and clusters with support for dense and sparse data.