6107 Repositories
Python From-Machine-Learning-Models-To-WebAPI Libraries
MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc.
MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc. ⭐⭐⭐⭐⭐
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
This repository holds the implementation for paper Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach Download our preproc
This repository contains learning resources for Python Fast API Framework and Docker
This repository contains learning resources for Python Fast API Framework and Docker, Build High Performing Apps With Python BootCamp by Lux Academy and Data Science East Africa.
A collection of online resources to help you on your Tech journey.
Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di
Code accompanying paper: Meta-Learning to Improve Pre-Training
Meta-Learning to Improve Pre-Training This folder contains code to run experiments in the paper Meta-Learning to Improve Pre-Training, NeurIPS 2021. P
Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"
Adversarial Neuron Pruning Purifies Backdoored Deep Models Code for NeurIPS 2021 "Adversarial Neuron Pruning Purifies Backdoored Deep Models" by Dongx
Scikit-Learn useful pre-defined Pipelines Hub
Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in
Indices Matter: Learning to Index for Deep Image Matting
IndexNet Matting This repository includes the official implementation of IndexNet Matting for deep image matting, presented in our paper: Indices Matt
Official repository for the paper F, B, Alpha Matting
FBA Matting Official repository for the paper F, B, Alpha Matting. This paper and project is under heavy revision for peer reviewed publication, and s
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert
Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration
Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration
CoGAIL Table of Content Overview Installation Dataset Training Evaluation Trained Checkpoints Acknowledgement Citations License Overview This reposito
(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"
SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
In the case of your data having only 1 channel while want to use timm models
timm_custom Description In the case of your data having only 1 channel while want to use timm models (with or without pretrained weights), run the fol
Official Repo of my work for SREC Nandyal Machine Learning Bootcamp
About the Bootcamp A 3-day Machine Learning Bootcamp organised by Department of Electronics and Communication Engineering, Santhiram Engineering Colle
YOLOv4-v3 Training Automation API for Linux
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects
CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Cookiecutter Data Science A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. Project homepage
PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)
PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to
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
Deep Learning Pipelines for Apache Spark
Deep Learning Pipelines for Apache Spark The repo only contains HorovodRunner code for local CI and API docs. To use HorovodRunner for distributed tra
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries. Documenta
A Python Implementation for Git for learning
A pure Python implementation for Git based on Buliding Git
A model checker for verifying properties in epistemic models
Epistemic Model Checker This is a model checker for verifying properties in epistemic models. The goal of the model checker is to check for Pluralisti
BudouX is the successor to Budou, the machine learning powered line break organizer tool.
BudouX Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning powered line break organizer tool. It is standalone
GUI for TOAD-GAN, a PCG-ML algorithm for Token-based Super Mario Bros. Levels.
If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Bootstrap Your Own Latent (BYOL), in Pytorch Practical implementation of an astoundingly simple method for self-supervised learning that achieves a ne
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is
Keyword spotting on Arm Cortex-M Microcontrollers
Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Si Adek Keras is software VR dangerous object detection.
Si Adek Python Keras Sistem Informasi Deteksi Benda Berbahaya Keras Python. Version 1.0 Developed by Ananda Rauf Maududi. Developed date: 24 November
Source code for CVPR 2020 paper "Learning to Forget for Meta-Learning"
L2F - Learning to Forget for Meta-Learning Sungyong Baik, Seokil Hong, Kyoung Mu Lee Source code for CVPR 2020 paper "Learning to Forget for Meta-Lear
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF This is an implementation of the CVPR '19 paper "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation" by Park et a
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur
Learning Correspondence from the Cycle-consistency of Time (CVPR 2019)
TimeCycle Code for Learning Correspondence from the Cycle-consistency of Time (CVPR 2019, Oral). The code is developed based on the PyTorch framework,
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods
ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).
Code for Active Learning at The ImageNet Scale.
Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.
This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.
RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models
TeST: Temporal-Stable Thresholding for Semi-supervised Learning
TeST: Temporal-Stable Thresholding for Semi-supervised Learning TeST Illustration Semi-supervised learning (SSL) offers an effective method for large-
Yaml - Loggers are like print() statements
Upgrade your print statements Loggers are like print() statements except they also include loads of other metadata: timestamp msg (same as print!) arg
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
Code for text augmentation method leveraging large-scale language models
HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P
TensorFlow port of PyTorch Image Models (timm) - image models with pretrained weights.
TensorFlow-Image-Models Introduction Usage Models Profiling License Introduction TensorfFlow-Image-Models (tfimm) is a collection of image models with
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems
PowerGridworld provides users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environments that readily integrate with existing training frameworks for reinforcement learning (RL).
Multi-Agent Reinforcement Learning (MARL) method to learn scalable control polices for multi-agent target tracking.
scalableMARL Scalable Reinforcement Learning Policies for Multi-Agent Control CD. Hsu, H. Jeong, GJ. Pappas, P. Chaudhari. "Scalable Reinforcement Lea
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021 Abstract Recent works have made great success in semantic segmentation by explo
BOF-Roaster is an automated buffer overflow exploit machine which is begin written with Python 3.
BOF-Roaster is an automated buffer overflow exploit machine which is begin written with Python 3. On first release it was able to successfully break many of the most well-known buffer overflow example executables.
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Official code of APHYNITY Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting (ICLR 2021, Oral) Yuan Yin*, Vincent Le Guen*
Code for Paper Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning
Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning (c) Tianyu Han and Daniel Truhn, RWTH Aachen University, 20
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v
Semi-Supervised Learning for Fine-Grained Classification
Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G
Self-Regulated Learning for Egocentric Video Activity Anticipation
Self-Regulated Learning for Egocentric Video Activity Anticipation Introduction This is a Pytorch implementation of the model described in our paper:
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'
Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang code will be released soon
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21)
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21) Citation If y
Efficient semidefinite bounds for multi-label discrete graphical models.
Low rank solvers #################################### benchmark/ : folder with the random instances used in the paper. ############################
Code for testing convergence rates of Lipschitz learning on graphs
📈 LipschitzLearningRates The code in this repository reproduces the experimental results on convergence rates for k-nearest neighbor graph infinity L
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling".
PSSL Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling". It consists of the pre-tra
Reproduced Code for Image Forgery Detection papers.
Image Forgery Detection With over 4.5 billion active internet users, the amount of multimedia content being shared every day has surpassed everyone’s
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体中文 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
OpenMMLab Image Classification Toolbox and Benchmark
Introduction English | 简体中文 MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. D
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas
VGGVox models for Speaker Identification and Verification trained on the VoxCeleb (1 & 2) datasets
VGGVox models for speaker identification and verification This directory contains code to import and evaluate the speaker identification and verificat
A minimal solution to hand motion capture from a single color camera at over 100fps. Easy to use, plug to run.
Minimal Hand A minimal solution to hand motion capture from a single color camera at over 100fps. Easy to use, plug to run. This project provides the
Code release for Local Light Field Fusion at SIGGRAPH 2019
Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion
A colab notebook for training Stylegan2-ada on colab, transfer learning onto your own dataset.
Stylegan2-Ada-Google-Colab-Starter-Notebook A no thrills colab notebook for training Stylegan2-ada on colab. transfer learning onto your own dataset h
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:
🧪 Cutting-edge experimental spaCy components and features
spacy-experimental: Cutting-edge experimental spaCy components and features This package includes experimental components and features for spaCy v3.x,
Anytime Learning At Macroscale
On Anytime Learning At Macroscale Learning from sequential data dumps (key) Requirements Python 3.7 Pytorch 1.9.0 Hydra 1.1.0 (pip install hydra-core
Code for DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Pytorch Implementation for DisCo: Remedy Self-supervi
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
Learning Logic Rules for Document-Level Relation Extraction
LogiRE Learning Logic Rules for Document-Level Relation Extraction We propose to introduce logic rules to tackle the challenges of doc-level RE. Equip
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati
Official Pytorch implementation of "DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network" (CVPR'21)
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye
Self-Supervised Document-to-Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control
Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
This is a Blender 2.9 script for importing mixamo Models to Godot-3
Mixamo-To-Godot This is a Blender 2.9 script for importing mixamo Models to Godot-3 The script does the following things Imports the mixamo models fro
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Repository of best practices for deep learning in Julia, inspired by fastai
FastAI Docs: Stable | Dev FastAI.jl is inspired by fastai, and is a repository of best practices for deep learning in Julia. Its goal is to easily ena
The fastai book, published as Jupyter Notebooks
English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc
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-
FasterAI: A library to make smaller and faster models with FastAI.
Fasterai fasterai is a library created to make neural network smaller and faster. It essentially relies on common compression techniques for networks
🔊 Audio and fastai v2
Fastaudio An audio module for fastai v2. We want to help you build audio machine learning applications while minimizing the need for audio domain expe
Walk with fastai
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, and deploy transformer specific models.
blurr A library that integrates huggingface transformers with version 2 of the fastai framework Install You can now pip install blurr via pip install
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q
A fastai/PyTorch package for unpaired image-to-image translation.
Unpaired image-to-image translation A fastai/PyTorch package for unpaired image-to-image translation currently with CycleGAN implementation. This is a
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
A modular domain adaptation library written in PyTorch.
A modular domain adaptation library written in PyTorch.
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
MSVCL_MICCAI2021 Installation Please follow the instruction in pytorch-CycleGAN-and-pix2pix to install. Example Usage An example of vendor-styles tran
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"
Multi Camera Pig Tracking Official Implementation of Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras CVPR2021 CV4Animals Workshop P
Creating multimodal multitask models
Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test
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
Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors
PSML paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors PSML_IONE,PSML_ABNE,PSML_DEEPLINK,PSML_SNNA: numpy
MLJetReconstruction - using machine learning to reconstruct jets for CMS
MLJetReconstruction - using machine learning to reconstruct jets for CMS The C++ data extraction code used here was based heavily on that foundv here.