5580 Repositories
Python deep-reinforcement-learning Libraries
ETNA â time series forecasting framework
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
mmfewshot is an open source few shot learning toolbox based on PyTorch
OpenMMLab FewShot Learning Toolbox and Benchmark
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)
To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/
Python module for data science and machine learning users.
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
A Powerful Serverless Analysis Toolkit That Takes Trial And Error Out of Machine Learning Projects
KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst
Detectron2 for Document Layout Analysis
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open
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
[AAAI2021] The source code for our paper ãEnhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motionã.
DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li
An Active Automata Learning Library Written in Python
AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core
Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows
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
Speedy Implementation of Instance-based Learning (IBL) agents in Python
A Python library to create single or multi Instance-based Learning (IBL) agents that are built based on Instance Based Learning Theory (IBLT) 1 Instal
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data ð
Rainbow ð An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat
Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication"
NFFT4ANOVA Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication" This package uses th
TransMorph: Transformer for Medical Image Registration
TransMorph: Transformer for Medical Image Registration keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registrati
UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring
UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Code Summary aggregate.py: this script aggr
Learning Neural Painters Fast! using PyTorch and Fast.ai
The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme
Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing"
ProxyFL Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing" Authors: Shivam Kalra*, Junfeng Wen*, Jess
Learning Versatile Neural Architectures by Propagating Network Codes
Learning Versatile Neural Architectures by Propagating Network Codes Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang, Zhiwu Lu, Jingdong Wang,
Deep Learning with PyTorch made easy ð !
Deep Learning with PyTorch made easy ð ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
A basic Ray Tracer that exploits numpy arrays and functions to work fast.
Python-Fast-Raytracer A basic Ray Tracer that exploits numpy arrays and functions to work fast. The code is written keeping as much readability as pos
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported
A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
torchsynth The fastest synth in the universe. Introduction torchsynth is based upon traditional modular synthesis written in pytorch. It is GPU-option
DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. â Star us on GitHub â it helps!! Frameworks & Librari
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure
Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b
TensorFlow implementation of Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction)
Barlow-Twins-TF This repository implements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrat
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo
Management of exclusive GPU access for distributed machine learning workloads
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
Convert Text-to Handwriting Using Python
Convert Text-to Handwriting Using Python Description In this project we'll use python library that's "pywhatkit" for converting text to handwriting. t
Codebase for "ProtoAttend: Attention-Based Prototypical Learning."
Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,
Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"
Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are
Stanza: A Python NLP Library for Many Human Languages
Official Stanford NLP Python Library for Many Human Languages
A crash course in six episodes for software developers who want to become machine learning practitioners.
Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P
Utilities for preprocessing text for deep learning with Keras
Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
Latex code for making neural networks diagrams
PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l
Code for the TCAV ML interpretability project
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C
Keras implementation of AdaBound
AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website ⢠Key Features ⢠How To Use ⢠Docs â¢
AI Toolkit for Healthcare Imaging
Medical Open Network for AI MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem. Its am
A distributed deep learning framework that supports flexible parallelization strategies.
FlexFlow FlexFlow is a deep learning framework that accelerates distributed DNN training by automatically searching for efficient parallelization stra
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl
Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).
Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.
SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S
Projeto: Machine Learning: Linguagens de Programacao 2004-2001
Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2
A Python step-by-step primer for Machine Learning and Optimization
early-ML Presentation General Machine Learning tutorials A Python step-by-step primer for Machine Learning and Optimization This github repository gat
Predicting the usefulness of reviews given the review text and metadata surrounding the reviews.
Predicting Yelp Review Quality Table of Contents Introduction Motivation Goal and Central Questions The Data Data Storage and ETL EDA Data Pipeline Da
A machine learning project that predicts the price of used cars in the UK
Car Price Prediction Image Credit: AA Cars Project Overview Scraped 3000 used cars data from AA Cars website using Python and BeautifulSoup. Cleaned t
DeepFaceLab fork which provides IPython Notebook to use DFL with Google Colab
DFL-Colab â DeepFaceLab fork for Google Colab This project provides you IPython Notebook to use DeepFaceLab with Google Colaboratory. You can create y
Multiple implementations for abstractive text summurization , using google colab
Text Summarization models if you are able to endorse me on Arxiv, i would be more than glad https://arxiv.org/auth/endorse?x=FRBB89 thanks This repo i
BERT score for text generation
BERTScore Automatic Evaluation Metric described in the paper BERTScore: Evaluating Text Generation with BERT (ICLR 2020). News: Features to appear in
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Introduction XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective.
Machine learning notebooks in different subjects optimized to run in google collaboratory
Notebooks Name Description Category Link Training pix2pix This notebook shows a simple pipeline for training pix2pix on a simple dataset. Most of the
Lab Materials for MIT 6.S191: Introduction to Deep Learning
This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available
Deep learning for NLP crash course at ABBYY.
Deep NLP Course at ABBYY Deep learning for NLP crash course at ABBYY. Suggested textbook: Neural Network Methods in Natural Language Processing by Yoa
Deep Learning tutorials in jupyter notebooks.
DeepSchool.io Sign up here for Udemy Course on Machine Learning (Use code DEEPSCHOOL-MARCH to get 85% off course). Goals Make Deep Learning easier (mi
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning
TensorFlow Tutorials with YouTube Videos
TensorFlow Tutorials Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction These tutorials are intended for beginne
Python solutions to solve practical business problems.
Python Business Analytics Also instead of "watching" you can join the link-letter, it's already being sent out to about 90 people and you are free to
Source for the paper "Universal Activation Function for machine learning"
Universal Activation Function Tensorflow and Pytorch source code for the paper Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal acti
Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors
By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated
Clinica is a software platform for clinical research studies involving patients with neurological and psychiatric diseases and the acquisition of multimodal data
Clinica Software platform for clinical neuroimaging studies Homepage | Documentation | Paper | Forum | See also: AD-ML, AD-DL ClinicaDL About The Proj
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
MRQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) data.
Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr
Python Automated Machine Learning library for tabular data.
Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie
Biterm Topic Model (BTM): modeling topics in short texts
Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua
K-Means clusternig example with Python and Scikit-learn
Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se
Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface
pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla
A desktop GUI providing an audio interface for GPT3.
Jabberwocky neil_degrasse_tyson_with_audio.mp4 Project Description This GUI provides an audio interface to GPT-3. My main goal was to provide a conven
Data Version Control or DVC is an open-source tool for data science and machine learning projects
Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj
Binary LSTM model for text classification
Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re
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
A machine learning model for analyzing text for user sentiment and determine whether its a positive, neutral, or negative review.
Sentiment Analysis on Yelp's Dataset Author: Roberto Sanchez, Talent Path: D1 Group Docker Deployment: Deployment of this application can be found her
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.
Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
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
Apply different text recognition services to images of handwritten documents.
Handprint The Handwritten Page Recognition Test is a command-line program that invokes HTR (handwritten text recognition) services on images of docume
AI-powered literature discovery and review engine for medical/scientific papers
AI-powered literature discovery and review engine for medical/scientific papers paperai is an AI-powered literature discovery and review engine for me
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
An interactive dashboard for visualisation, integration and classification of data using Active Learning.
AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-
This repository contains code for building education startup.
Learning Management System Overview It's the code for EssayBrain, a tool for teacher that automatically grades and validates essays. In order to valid
Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python
FlappyAI Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python Everything Used Genetic Algorithm especially NEAT conce
topic modeling on unstructured data in Space news articles retrieved from the Guardian (UK) newspaper using API
NLP Space News Topic Modeling Photos by nasa.gov (1, 2, 3, 4, 5) and extremetech.com Table of Contents Project Idea Data acquisition Primary data sour
Real-time analysis of intracranial neurophysiology recordings.
py_neuromodulation Click this button to run the "Tutorial ML with py_neuro" notebooks: The py_neuromodulation toolbox allows for real time capable pro
Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.
Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.
This project uses unsupervised machine learning to identify correlations between daily inoculation rates in the USA and twitter sentiment in regards to COVID-19.
Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro
piSTAR Lab is a modular platform built to make AI experimentation accessible and fun. (pistar.ai)
piSTAR Lab WARNING: This is an early release. Overview piSTAR Lab is a modular deep reinforcement learning platform built to make AI experimentation a
Accelerating model creation and evaluation.
EmeraldML A machine learning library for streamlining the process of (1) cleaning and splitting data, (2) training, optimizing, and testing various mo
There are some basic arithmatic in Pattern Recognization and Machine Learning writed in Python in this repository
There are some basic arithmatic in Pattern Recognization and Machine Learning writed in Python in this repository
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection Introduction This repository includes codes and models of "Effect of De
Video Corpus Moment Retrieval with Contrastive Learning (SIGIR 2021)
Video Corpus Moment Retrieval with Contrastive Learning PyTorch implementation for the paper "Video Corpus Moment Retrieval with Contrastive Learning"