Python D-optimal-recommender-selection Resources

AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems and automatically guides the design of experiment to be evaluated.

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021

OTA: Optimal Transport Assignment for Object Detection This project provides an implementation for our CVPR2021 paper "OTA: Optimal Transport Assignme

FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa

sklearn-genetic Genetic feature selection module for scikit-learn Genetic algorithms mimic the process of natural selection to search for optimal valu

Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,

BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l

boruta_py This project hosts Python implementations of the Boruta all-relevant feature selection method. Related blog post How to install Install with

scikit-feature Feature selection repository scikit-feature in Python. scikit-feature is an open-source feature selection repository in Python develope

Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

TensorRec A TensorFlow recommendation algorithm and framework in Python. NOTE: TensorRec is not under active development TensorRec will not be receivi

Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with th

Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin

LightFM Build status Linux OSX (OpenMP disabled) Windows (OpenMP disabled) LightFM is a Python implementation of a number of popular recommendation al

Implicit Fast Python Collaborative Filtering for Implicit Datasets. This project provides fast Python implementations of several different popular rec

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

Cornac Cornac is a comparative framework for multimodal recommender systems. It focuses on making it convenient to work with models leveraging auxilia

Recommenders What's New (February 4, 2021) We have a new relase Recommenders 2021.2! It comes with lots of bug fixes, optimizations and 3 new algorith

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

python-recsys A python library for implementing a recommender system. Installation Dependencies python-recsys is build on top of Divisi2, with csc-pys

Crab - A Recommendation Engine library for Python Crab is a flexible, fast recommender engine for Python that integrates classic information filtering r

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear