471 Repositories
Python sorting-algorithms Libraries
PyTorch implementation of Deformable Convolution
PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple
Implementation of algorithms for continuous control (DDPG and NAF).
DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.
Rafael Project- Classifying rockets to different types using data science algorithms.
Rocket-Classify Rafael Project- Classifying rockets to different types using data science algorithms. In this project we received data base with data
Entropy-controlled contexts in Python
Python module ordered ordered module is the opposite to random - it maintains order in the program. import random x = 5 def increase(): global x
In this Github repository I will share my freqtrade files with you. I want to help people with this repository who don't know Freqtrade so much yet.
My Freqtrade stuff In this Github repository I will share my freqtrade files with you. I want to help people with this repository who don't know Freqt
Solving a card game with three search algorithms: BFS, IDS, and A*
Search Algorithms Overview In this project, we want to solve a card game with three search algorithms. In this card game, we have to sort our cards by
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.
Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo
Sorting Algorithm Visualiser using pygame
SortingVisualiser Sorting Algorithm Visualiser using pygame Features Visualisation of some traditional sorting algorithms like quicksort and bubblesor
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the
zoofs is a Python library for performing feature selection using an variety of nature inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics based to Evolutionary. It's easy to use ,flexible and powerful tool to reduce your feature size.
zoofs is a Python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
Visualizations of linear algebra algorithms for people who want a deep understanding
Visualising algorithms on symmetric matrices Examples QR algorithm and LR algorithm Here, we have a GIF animation of an interactive visualisation of t
A Python package implementing various colour checker detection algorithms and related utilities.
A Python package implementing various colour checker detection algorithms and related utilities.
This is the code repository for 40 Algorithms Every Programmer Should Know , published by Packt.
40 Algorithms Every Programmer Should Know, published by Packt
Pytorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.
Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.
A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search (Manhattan Distance Heuristic)
A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod
An all-in-one application to visualize multiple different local path planning algorithms
Table of Contents Table of Contents Local Planner Visualization Project (LPVP) Features Installation/Usage Local Planners Probabilistic Roadmap (PRM)
Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Real-ESRGAN Colab Demo for Real-ESRGAN . Portable Windows executable file. You can find more information here. Real-ESRGAN aims at developing Practica
PyTorch implementations of algorithms for density estimation
pytorch-flows A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invert
PyTorch implementations of deep reinforcement learning algorithms and environments
Deep Reinforcement Learning Algorithms with PyTorch This repository contains PyTorch implementations of deep reinforcement learning algorithms and env
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an
Решения, подсказки, тесты и утилиты для тренировки по алгоритмам от Яндекса.
Решения и подсказки к тренировке по алгоритмам от Яндекса Что есть внутри Решения с подсказками и комментариями; рекомендую сначала смотреть md файл п
A collection of research papers and software related to explainability in graph machine learning.
A collection of research papers and software related to explainability in graph machine learning.
DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms
DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme
MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees.
MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives.
Automated modeling and machine learning framework FEDOT
This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML). It can build custom modeling pipelines for different real-world processes in an automated way using an evolutionary approach. FEDOT supports classification (binary and multiclass), regression, clustering, and time series prediction tasks.
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop a ecosystem to experiment, share, reproduce, and deploy in real world in a smooth and easy way (Hope it can be done).
30 Days Of Machine Learning Using Pytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
ML Optimizers from scratch using JAX
Toy implementations of some popular ML optimizers using Python/JAX
State-of-the-art data augmentation search algorithms in PyTorch
MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal
A Curated Collection of Awesome Python Scripts
A Curated Collection of Awesome Python Scripts that will make you go wow. This repository will help you in getting those green squares. Hop in and enjoy the journey of open source. 🚀
Multi Agent Path Finding Algorithms
MATP-solver Simulator collision check path step random initial states or given states Traditional method Seperate A* algorithem Confict-based Search S
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
Code release to accompany paper "Geometry-Aware Gradient Algorithms for Neural Architecture Search."
Geometry-Aware Gradient Algorithms for Neural Architecture Search This repository contains the code required to run the experiments for the DARTS sear
A New, Interactive Approach to Learning Python
This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models and supports classification, regression and ranking. TF-DF is a TensorFlow wrapper around the Yggdrasil Decision Forests C++ libraries. Models trained with TF-DF are compatible with Yggdrasil Decision Forests' models, and vice versa.
An Unsupervised Graph-based Toolbox for Fraud Detection
An Unsupervised Graph-based Toolbox for Fraud Detection Introduction: UGFraud is an unsupervised graph-based fraud detection toolbox that integrates s
Python sample codes for robotics algorithms.
PythonRobotics Python codes for robotics algorithm. Table of Contents What is this? Requirements Documentation How to use Localization Extended Kalman
Hide Your Secret Message in any Wave Audio File.
HiddenWave Embedding secret messages in wave audio file What is HiddenWave Hiddenwave is a python based program for simple audio steganography. You ca
A genetic algorithm written in Python for educational purposes.
Genea: A Genetic Algorithm in Python Genea is a Genetic Algorithm written in Python, for educational purposes. I started writing it for fun, while lea
A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making
Fast, differentiable sorting and ranking in PyTorch
Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms
Visual Tracking by TridenAlign and Context Embedding
Visual Tracking by TridentAlign and Context Embedding (TACT) Test code for "Visual Tracking by TridentAlign and Context Embedding" Janghoon Choi, Juns
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms This repo contains the source code to reproduce the results in the paper A Close
Implementation of different ML Algorithms from scratch, written in Python 3.x
Implementation of different ML Algorithms from scratch, written in Python 3.x
A command line tool for memorizing algorithms in Python by typing them.
Algo Drills A command line tool for memorizing algorithms in Python by typing them. In alpha and things will change. How it works Type out an algorith
Speech Algorithms Collections
Speech Algorithms Collections
A tf.keras implementation of Facebook AI's MadGrad optimization algorithm
MADGRAD Optimization Algorithm For Tensorflow This package implements the MadGrad Algorithm proposed in Adaptivity without Compromise: A Momentumized,
Plug-n-Play Reinforcement Learning in Python with OpenAI Gym and JAX
coax is built on top of JAX, but it doesn't have an explicit dependence on the jax python package. The reason is that your version of jaxlib will depend on your CUDA version.
mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms.
mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility functions that allow writing model-based RL algorithms with only a few lines of code.
A Python library created to assist programmers with complex mathematical functions
libmaths libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat
isort is a Python utility / library to sort imports alphabetically, and automatically separated into sections and by type.
isort is a Python utility / library to sort imports alphabetically, and automatically separated into sections and by type. It provides a command line utility, Python library and plugins for various editors to quickly sort all your imports.
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Faster R-CNN and Mask R-CNN in PyTorch 1.0 maskrcnn-benchmark has been deprecated. Please see detectron2, which includes implementations for all model
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
AdvancedHMC.jl AdvancedHMC.jl provides a robust, modular and efficient implementation of advanced HMC algorithms. An illustrative example for Advanced
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
The SLIDE package contains the source code for reproducing the main experiments in this paper. Dataset The Datasets can be downloaded in Amazon-
Predict stock movement with Machine Learning and Deep Learning algorithms
Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th
Use deep learning, genetic programming and other methods to predict stock and market movements
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
Trading environnement for RL agents, backtesting and training.
TradzQAI Trading environnement for RL agents, backtesting and training. Live session with coinbasepro-python is finaly arrived ! Available sessions: L
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
Trading Gym Trading Gym is an open-source project for the development of reinforcement learning algorithms in the context of trading. It is currently
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
An open-source library of algorithms to analyse time series in GPU and CPU.
An open-source library of algorithms to analyse time series in GPU and CPU.
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Simple yet flexible natural sorting in Python.
natsort Simple yet flexible natural sorting in Python. Source Code: https://github.com/SethMMorton/natsort Downloads: https://pypi.org/project/natsort
An introduction of Markov decision process (MDP) and two algorithms that solve MDPs (value iteration, policy iteration) along with their Python implementations.
Markov Decision Process A Markov decision process (MDP), by definition, is a sequential decision problem for a fully observable, stochastic environmen
Multivariate imputation and matrix completion algorithms implemented in Python
A variety of matrix completion and imputation algorithms implemented in Python 3.6. To install: pip install fancyimpute Do not use conda. We don't sup
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A
cuML - RAPIDS Machine Learning Library
cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t
cuDF - GPU DataFrame Library
cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Resources cuDF Reference Documentation: Python API refe
Distributed Evolutionary Algorithms in Python
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Find big moving stocks before they move using machine learning and anomaly detection
Surpriver - Find High Moving Stocks before they Move Find high moving stocks before they move using anomaly detection and machine learning. Surpriver
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
Backtesting.py Backtest trading strategies with Python. Project website Documentation the project if you use it. Installation $ pip install backtestin
Common financial technical indicators implemented in Pandas.
FinTA (Financial Technical Analysis) Common financial technical indicators implemented in Pandas. This is work in progress, bugs are expected and resu
[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro
Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms
Open-L2O This repository establishes the first comprehensive benchmark efforts of existing learning to optimize (L2O) approaches on a number of proble
A lightweight file-copying interface.
autosort A lightweight file-copying interface. Preview What is autosort? Autosort is a lightweight file-copying interface. It allows you to copy sever
Pre-Recognize Library - library with algorithms for improving OCR quality.
PRLib - Pre-Recognition Library. The main aim of the library - prepare image for recogntion. Image processing can really help to improve recognition q
A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約
Scene Text Localization & Recognition Resources Read this institute-wise: English, 简体中文. Read this year-wise: English, 简体中文. Tags: [STL] (Scene Text L
The first open-source library that detects the font of a text in a image.
Typefont Typefont is an experimental library that detects the font of a text in a image. Usage Import the main function and invoke it like in the foll
[ICLR 2021] Is Attention Better Than Matrix Decomposition?
Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T
An experimental code editor for writing algorithms
Algojammer Algojammer is an experimental, proof-of-concept code editor for writing algorithms in Python. It was mainly written to assist with solving
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A mini library for Policy Gradients with Parameter-based Exploration, with reference implementation of the ClipUp optimizer from NNAISENSE.
PGPElib A mini library for Policy Gradients with Parameter-based Exploration [1] and friends. This library serves as a clean re-implementation of the
All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.
Data Structures and Algorithms Python INDEX 1. Resources - Books Data Structures - Reema Thareja competitiveCoding Big-O Cheat Sheet DAA Syllabus Inte
This is the official implementation of Multi-Agent PPO.
MAPPO Chao Yu*, Akash Velu*, Eugene Vinitsky, Yu Wang, Alexandre Bayen, and Yi Wu. Website: https://sites.google.com/view/mappo This repository implem
Scripts of Machine Learning Algorithms from Scratch. Implementations of machine learning models and algorithms using nothing but NumPy with a focus on accessibility. Aims to cover everything from basic to advance.
Algo-ScriptML Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The goal of this project is not t
library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization
NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi
A research toolkit for particle swarm optimization in Python
PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python. It is intended for swarm intelligence researchers, practit
🎯 A comprehensive gradient-free optimization framework written in Python
Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not
Use evolutionary algorithms instead of gridsearch in scikit-learn
sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to reduce the time required to find the best parameter
Distributed Evolutionary Algorithms in Python
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Dopamine Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grok
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning. TF-Agents makes implementing, de