656 Repositories
Python motion-planning-algorithms Libraries
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
Intruder detection systems are common place now, and readily available in industry, but how do they work? They must detect people and large animals, but not generate false alarms in the presence of small animals, changes in lighting, environmental motion such as trees, or melting snow. To work correctly, the system must learn the background, in order to differentiate foreground objects.
Intruder-Detection Intruder detection systems are common place now, and readily available in industry, but how do they work? They must detect people a
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
Detection of drones using their thermal signatures from thermal camera through YOLO-V3 based CNN with modifications to encapsulate drone motion
Drone Detection using Thermal Signature This repository highlights the work for night-time drone detection using a using an Optris PI Lightweight ther
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.
Official implementation of the network presented in the paper "M4Depth: A motion-based approach for monocular depth estimation on video sequences"
M4Depth This is the reference TensorFlow implementation for training and testing depth estimation models using the method described in M4Depth: A moti
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.
[WACV 2020] Reducing Footskate in Human Motion Reconstruction with Ground Contact Constraints
Reducing Footskate in Human Motion Reconstruction with Ground Contact Constraints Official implementation for Reducing Footskate in Human Motion Recon
PyTorch implementation DRO: Deep Recurrent Optimizer for Structure-from-Motion
DRO: Deep Recurrent Optimizer for Structure-from-Motion This is the official PyTorch implementation code for DRO-sfm. For technical details, please re
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
GanTTY - Project planning from the terminal
GanTTY - Project planning from the terminal
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
The ABR Control library is a python package for the control and path planning of robotic arms in real or simulated environments.
The ABR Control library is a python package for the control and path planning of robotic arms in real or simulated environments. ABR Control provides API's for the Mujoco, CoppeliaSim (formerly known as VREP), and Pygame simulation environments, and arm configuration files for one, two, and three-joint models, as well as the UR5 and Kinova Jaco 2 arms. Users can also easily extend the package to run with custom arm configurations. ABR Control auto-generates efficient C code for generating the control signals, or uses Mujoco's internal functions to carry out the calculations.
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
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
Unofficial & improved implementation of NeRF--: Neural Radiance Fields Without Known Camera Parameters
[Unofficial code-base] NeRF--: Neural Radiance Fields Without Known Camera Parameters [ Project | Paper | Official code base ] ⬅️ Thanks the original
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
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021
TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r
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.
Synthesizing Long-Term 3D Human Motion and Interaction in 3D in CVPR2021
Long-term-Motion-in-3D-Scenes This is an implementation of the CVPR'21 paper "Synthesizing Long-Term 3D Human Motion and Interaction in 3D". Please ch
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
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
OSMnx: Python for street networks. Retrieve, model, analyze, and visualize street networks and other spatial data from OpenStreetMap.
OSMnx OSMnx is a Python package that lets you download geospatial data from OpenStreetMap and model, project, visualize, and analyze real-world street
Learning to Estimate Hidden Motions with Global Motion Aggregation
Learning to Estimate Hidden Motions with Global Motion Aggregation (GMA) This repository contains the source code for our paper: Learning to Estimate
Official repository for "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation"
pair-emnlp2020 Official repository for the paper: Xinyu Hua and Lu Wang: PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long
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 :)
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
[arXiv] What-If Motion Prediction for Autonomous Driving ❓🚗💨
WIMP - What If Motion Predictor Reference PyTorch Implementation for What If Motion Prediction [PDF] [Dynamic Visualizations] Setup Requirements The W
dataset for ECCV 2020 "Motion Capture from Internet Videos"
Motion Capture from Internet Videos Motion Capture from Internet Videos Junting Dong*, Qing Shuai*, Yuanqing Zhang, Xian Liu, Xiaowei Zhou, Hujun Bao
[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
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.
Character Controllers using Motion VAEs
Character Controllers using Motion VAEs This repo is the codebase for the SIGGRAPH 2020 paper with the title above. Please find the paper and demo at
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
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)
Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O
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
Object Depth via Motion and Detection Dataset
ODMD Dataset ODMD is the first dataset for learning Object Depth via Motion and Detection. ODMD training data are configurable and extensible, with ea
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
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Status: Maintenance (expect bug fixes and minor updates) Baselines OpenAI Baselines is a set of high-quality implementations of reinforcement learning
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,
A fast xgboost feature selection algorithm
BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l
cuDF - GPU DataFrame Library
cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Built based on the Apache Arrow columnar memory format,
A library that implements fairness-aware machine learning algorithms
Themis ML themis-ml is a Python library built on top of pandas and sklearnthat implements fairness-aware machine learning algorithms. Fairness-aware M
Algorithms for monitoring and explaining machine learning models
Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual
How on earth can I ever think of a solution like that in an interview?!
fuck-coding-interviews This repository is created by an awkward programmer who always struggles with coding problems on LeetCode, even with some Easy
Algorithms and data structures for educational, demonstrational and experimental purposes.
Algorithms and Data Structures (ands) Introduction This project was created for personal use mostly while studying for an exam (starting in the month
Algorithms implemented in Python
Python Algorithms Library Laurent Luce Description The purpose of this library is to help you with common algorithms like: A* path finding. String Mat
:computer: Data Structures and Algorithms in Python
Algorithms in Python Implementations of a few algorithms and datastructures for fun and profit! Completed Karatsuba Multiplication Basic Sorting Rabin
This repository is not maintained
This repository is no longer maintained, but is being kept around for educational purposes. If you want a more complete algorithms repo check out: htt
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Python-based implementations of algorithms for learning on imbalanced data.
ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn
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
Uplift modeling and causal inference with machine learning algorithms
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
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 modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
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