587 Repositories
Python recommendation-algorithms Libraries
Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation
Tiny-NewsRec The source codes for our paper "Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation". Requirements PyTorch == 1.6.0 Tensor
Adaptive Denoising Training (ADT) for Recommendation.
DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h
Stenography encryption script
ImageCrypt Project description Installation Usage Project description Project AlexGyver on Python by TheK4n Design by Пашушка Byte packing in decimal
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators
Pandas TA - A Technical Analysis Library in Python 3 Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package
Contra is a lightweight, production ready Tensorflow alternative for solving time series prediction challenges with AI
Contra AI Engine A lightweight, production ready Tensorflow alternative developed by Styvio styvio.com » How to Use · Report Bug · Request Feature Tab
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
Overview This repository implemented some common motion planners used on autonomous vehicles, including Hybrid A* Planner Frenet Optimal Trajectory Hi
Pytorch domain library for recommendation systems
TorchRec (Experimental Release) TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale
sudoku solver using CSP forward-tracking algorithms.
Sudoku sudoku solver using CSP forward-tracking algorithms. Description Sudoku is a logic-based game that consists of 9 3x3 grids that create one larg
Implementation of core NuPIC algorithms in C++
NuPIC Core This repository contains the C++ source code for the Numenta Platform for Intelligent Computing (NuPIC)
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
Research using Cirq!
ReCirq Research using Cirq! This project contains modules for running quantum computing applications and experiments through Cirq and Quantum Engine.
A selection of a few algorithms used to sort or search an array
Sort and search algorithms This repository has some common search / sort algorithms written in python, I also included the pseudocode of each algorith
FPE - Format Preserving Encryption with FF3 in Python
ff3 - Format Preserving Encryption in Python An implementation of the NIST approved FF3 and FF3-1 Format Preserving Encryption (FPE) algorithms in Pyt
Minimal pure Python library for working with little-endian list representation of bit strings.
bitlist Minimal Python library for working with bit vectors natively. Purpose This library allows programmers to work with a native representation of
Google, Facebook, Amazon, Microsoft, Netflix tech interview questions
Algorithm and Data Structures Interview Questions HackerRank | Practice, Tutorials & Interview Preparation Solutions This repository consists of solut
Learn to code in any language. If
Learn to Code It is an intiiative undertaken by Student Ambassadors Club, Jamshoro for students who are absolute begineers in programming and want to
Randomly picks between your favourite meals for you when you're feeling indecisive.
Food Recommendations Desktop application created with python and tkinter. The goal for this application is to provide a way for users to enter and sav
Convenient script for trading with python.
Convenient script for trading with python.
A library for implementing Decentralized Graph Neural Network algorithms.
decentralized-gnn A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes. De
Robust & Reliable Route Recommendation on Road Networks
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks This repository is the official implementation of NeuroMLR: Robust & Reliable Route
This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation withNoisy Multi-feedback"
Curriculum_disentangled_recommendation This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation with Noisy Multi-feedb
Visualisation for sorting algorithms. Version 2.0
Visualisation for sorting algorithms v2. Upped a notch from version 1. This program provides animates simple, common and popular sorting algorithms, t
Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)
Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)
Algorithm for Cutting Stock Problem using Google OR-Tools. Link to the tool:
Cutting Stock Problem Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually o
A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms
MatrixProfile MatrixProfile is a Python 3 library, brought to you by the Matrix Profile Foundation, for mining time series data. The Matrix Profile is
Various Algorithms for Short Text Mining
Short Text Mining in Python Introduction This package shorttext is a Python package that facilitates supervised and unsupervised learning for short te
The implementation of our CIKM 2021 paper titled as: "Cross-Market Product Recommendation"
FOREC: A Cross-Market Recommendation System This repository provides the implementation of our CIKM 2021 paper titled as "Cross-Market Product Recomme
An Unbiased Learning To Rank Algorithms (ULTRA) toolbox
Unbiased Learning to Rank Algorithms (ULTRA) This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiment
It is a platform that implements some path planning algorithms.
PathPlanningAlgorithms It is a platform that implements some path planning algorithms. Main dependence: python3.7, opencv4.1.1.26 (for image show) Tip
E-Commerce recommender demo with real-time data and a graph database
🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str
An index of algorithms for learning causality with data
awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{
High performance distributed framework for training deep learning recommendation models based on PyTorch.
PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Fast and simple implementation of RL algorithms, designed to run fully on GPU.
RSL RL Fast and simple implementation of RL algorithms, designed to run fully on GPU. This code is an evolution of rl-pytorch provided with NVIDIA's I
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.
ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in
A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.
TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction 论文:Time Interval Aware Sel
Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".
SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning
ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a
Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.
Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-
The Most Efficient Temporal Difference Learning Framework for 2048
moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize
⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co
Confidence intervals for scikit-learn forest algorithms
forest-confidence-interval: Confidence intervals for Forest algorithms Forest algorithms are powerful ensemble methods for classification and regressi
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
The source code and dataset for the RecGURU paper (WSDM 2022)
RecGURU About The Project Source code and baselines for the RecGURU paper "RecGURU: Adversarial Learning of Generalized User Representations for Cross
GNN-based Recommendation Benchmark
GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma
A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning
pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and
A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework
music-recommender-rest-api A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework How it works T
This is a Machine Learning model which predicts the presence of Diabetes in Patients
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
This Repository consists of my solutions in Python 3 to various problems in Data Structures and Algorithms
Problems and it's solutions. Problem solving, a great Speed comes with a good Accuracy. The more Accurate you can write code, the more Speed you will
Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms
Differential_Privacy_CPS Python implementation of the research paper Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms Re
iAWE is a wonderful dataset for those of us who work on Non-Intrusive Load Monitoring (NILM) algorithms.
iAWE is a wonderful dataset for those of us who work on Non-Intrusive Load Monitoring (NILM) algorithms. You can find its main page and description via this link. If you are familiar with NILM-TK API, you probably know that you can work with iAWE hdf5 data file in NILM-TK.
A Recommendation System For Diabetes Detection And Treatment
Diabetes-detection-tg-bot A Recommendation System For Diabetes Detection And Treatment Данная система помогает определить наличие или отсутствие сахар
A place where one-off ideas/partial projects can live comfortably
A place to post ideas, partial projects, or anything else that doesn't necessarily warrant its own repo, from my mind to the web.
Visualization of numerical optimization algorithms
Visualization of numerical optimization algorithms
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation
Python package for visualizing the loss landscape of parameterized quantum algorithms.
orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect
HashDB is a community-sourced library of hashing algorithms used in malware.
HashDB HashDB is a community-sourced library of hashing algorithms used in malware. How To Use HashDB HashDB can be used as a stand alone hashing libr
PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021.
PAML PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021. (Continuously updating ) Int
Metric learning algorithms in Python
metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met
A high performance implementation of HDBSCAN clustering.
HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates
PyClustering is a Python, C++ data mining library.
pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.
The Fundamental Clustering Problems Suite (FCPS) summaries 54 state-of-the-art clustering algorithms, common cluster challenges and estimations of the number of clusters as well as the testing for cluster tendency.
FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu
Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.
GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl
Machine learning algorithms implementation
Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen
High performance distributed framework for training deep learning recommendation models based on PyTorch.
High performance distributed framework for training deep learning recommendation models based on PyTorch.
Session-aware Item-combination Recommendation with Transformer Network
Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations Requirements python 3.6 torch 1.9 numpy 1.19 Quick Start The experimen
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.
Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif
Statistical and Algorithmic Investing Strategies for Everyone
Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Evol is clear dsl for composable evolutionary algorithms that optimised for joy.
Evol is clear dsl for composable evolutionary algorithms that optimised for joy. Installation We currently support python3.6 and python3.7 and you can
onelearn: Online learning in Python
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
CLI tool to computes CO2 emissions of HPC computations following green-algorithms.org methodology
gqueue gqueue is a CLI (command line interface) tool that computes carbon footprint of HPC computations on clusters running slurm. It follows the meth
Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.
TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De
PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.
Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik
Recommendation System to recommend top books from the dataset
recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als
A paper using optimal transport to solve the graph matching problem.
GOAT A paper using optimal transport to solve the graph matching problem. https://arxiv.org/abs/2111.05366 Repo structure .github: Files specifying ho
My dynamic programming algorithms for exercise and fun
My Dynamic Programming Algorithms giraycoskun [email protected] It is a repo for various dynamic programming algorithms for exercise.
Algorithms for calibrating power grid distribution system models
Distribution System Model Calibration Algorithms The code in this library was developed by Sandia National Laboratories under funding provided by the
Fair Recommendation in Two-Sided Platforms
Fair Recommendation in Two-Sided Platforms
Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks
Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks This is our Pytorch implementation for the paper: Zirui Zhu, Chen Gao, Xu C
Pytorch implementation for the paper: Contrastive Learning for Cold-start Recommendation
Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L
Parameterising Simulated Annealing for the Travelling Salesman Problem
Parameterising Simulated Annealing for the Travelling Salesman Problem
UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac protocols on unmanned aerial vehicle networks.
UAV-Networks Simulator - Autonomous Networking - A.A. 20/21 UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac pr
Deep Learning Based Fasion Recommendation System for Ecommerce
Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod
Parameterising Simulated Annealing for the Travelling Salesman Problem
Parameterising Simulated Annealing for the Travelling Salesman Problem Abstract The Travelling Salesman Problem is a well known NP-Hard problem. Given
Deep Learning Algorithms for Hedging with Frictions
Deep Learning Algorithms for Hedging with Frictions This repository contains the Forward-Backward Stochastic Differential Equation (FBSDE) solver and
Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback This is our Pytorch implementation for the paper: Yinwei Wei,
Implementation of popular bandit algorithms in batch environments.
batch-bandits Implementation of popular bandit algorithms in batch environments. Source code to our paper "The Impact of Batch Learning in Stochastic
UV matrix decompostion using movielens dataset
UV-matrix-decompostion-with-kfold UV matrix decompostion using movielens dataset upload the 'ratings.dat' file install the following python libraries
Implementation of association rules mining algorithms (Apriori|FPGrowth) using python.
Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in
Data science, Data manipulation and Machine learning package.
duality Data science, Data manipulation and Machine learning package. Use permitted according to the terms of use and conditions set by the attached l
scikit-multimodallearn is a Python package implementing algorithms multimodal data.
scikit-multimodallearn is a Python package implementing algorithms multimodal data. It is compatible with scikit-learn, a popul
PECOS - Prediction for Enormous and Correlated Spaces
PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i
PyTorch implementation for "Mining Latent Structures with Contrastive Modality Fusion for Multimedia Recommendation"
MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.