3088 Repositories
Python training-data Libraries
A library for uncertainty representation and training in neural networks.
Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte
Extract Thailand COVID-19 Cluster data from daily briefing pdf.
Thailand COVID-19 Cluster Data Extraction About Extract Clusters from Thailand Daily COVID-19 briefing PDF Download latest data Here. Data will be upd
This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust.
Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R
Universal End2End Training Platform, including pre-training, classification tasks, machine translation, and etc.
背景 安装教程 快速上手 (一)预训练模型 (二)机器翻译 (三)文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台,支持多种预训练方式,以及序列生成和自然语言理解任务。 安装教程 git clone git
Evidently helps analyze machine learning models during validation or production monitoring
Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
MASS: Masked Sequence to Sequence Pre-training for Language Generation
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Collect super-resolution related papers, data, repositories
Collect super-resolution related papers, data, repositories
Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in order to find the highest performing cryptocurrencies historically
crypto-performance-tracker Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in ord
Automated data scraper for Thailand COVID-19 data
The Researcher COVID data Automated data scraper for Thailand COVID-19 data Accessing the Data 1st Dose Provincial Vaccination Data 2nd Dose Provincia
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Random Erasing Data Augmentation =============================================================== black white random This code has the source code for
In-Place Activated BatchNorm for Memory-Optimized Training of DNNs
In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F
A curated list of amazingly awesome Cybersecurity datasets
A curated list of amazingly awesome Cybersecurity datasets
A python application for manipulating pandas data frames from the comfort of your web browser
A python application for manipulating pandas data frames from the comfort of your web browser. Data flows are represented as a Directed Acyclic Graph, and nodes can be ran individually as the user sees fit.
Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)
Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg
Anomaly detection on SQL data warehouses and databases
With CueObserve, you can run anomaly detection on data in your SQL data warehouses and databases. Getting Started Install via Docker docker run -p 300
Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxiang Wang, Han Zhao, Bo Li.
Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"
DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better This repository contains code to deduplicate language model datasets as descrbed in the paper
Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.
This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"
SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan
A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.
ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer
Utility functions for working with data from Nix in Python
Pynixutil - Utility functions for working with data from Nix in Python Examples Base32 encoding/decoding import pynixutil input = "v5sv61sszx301i0x6x
Python package for machine learning for healthcare using a OMOP common data model
This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.
NeuralCompression is a Python repository dedicated to research of neural networks that compress data
NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.
Rubrix is a free and open-source tool for exploring and iterating on data for artificial intelligence projects.
Open-source tool for exploring, labeling, and monitoring data for AI projects
A pytorch reproduction of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.
A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch
A certifiable defense against adversarial examples by training neural networks to be provably robust
DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the
DrQ-v2: Improved Data-Augmented Reinforcement Learning
DrQ-v2: Improved Data-Augmented RL Agent Method DrQ-v2 is a model-free off-policy algorithm for image-based continuous control. DrQ-v2 builds on DrQ,
Data exploration done quick.
Pandas Tab Implementation of Stata's tabulate command in Pandas for extremely easy to type one-way and two-way tabulations. Support: Python 3.7 and 3.
A library for generating fake data and populating database tables.
Knockoff Factory A library for generating mock data and creating database fixtures that can be used for unit testing. Table of content Installation Ch
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn
code and data for paper "GIANT: Scalable Creation of a Web-scale Ontology"
GIANT Code and data for paper "GIANT: Scalable Creation of a Web-scale Ontology" https://arxiv.org/pdf/2004.02118.pdf Please cite our paper if this pr
Self-training for Few-shot Transfer Across Extreme Task Differences
Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo
PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"
Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N
A new data augmentation method for extreme lighting conditions.
Random Shadows and Highlights This repo has the source code for the paper: Random Shadows and Highlights: A new data augmentation method for extreme l
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
RawVSR This repo contains the official codes for our paper: Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference Xiaoh
Official repository for the paper, MidiBERT-Piano: Large-scale Pre-training for Symbolic Music Understanding.
MidiBERT-Piano Authors: Yi-Hui (Sophia) Chou, I-Chun (Bronwin) Chen Introduction This is the official repository for the paper, MidiBERT-Piano: Large-
AlphaNet Improved Training of Supernet with Alpha-Divergence
AlphaNet: Improved Training of Supernet with Alpha-Divergence This repository contains our PyTorch training code, evaluation code and pretrained model
ONNX Runtime for PyTorch accelerates PyTorch model training using ONNX Runtime.
Accelerate PyTorch models with ONNX Runtime
MachineLearningStocks is designed to be an intuitive and highly extensible template project applying machine learning to making stock predictions.
Using python and scikit-learn to make stock predictions
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
The MLOps platform for innovators 🚀
DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.
Raganarok X: Next Generation Data Dump
Raganarok X Data Dump Raganarok X: Next Generation Data Dump More interesting Files File Name Contains en_langs All the variables you need in English
A Python library for reading, writing and visualizing the OMEGA Format
A Python library for reading, writing and visualizing the OMEGA Format, targeted towards storing reference and perception data in the automotive context on an object list basis with a focus on an urban use case.
Squidpy is a tool for the analysis and visualization of spatial molecular data.
Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.
A community run, 5-day PyTorch Deep Learning Bootcamp
Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
🛠 All-in-one web-based IDE specialized for machine learning and data science.
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
HyperPose is a library for building high-performance custom pose estimation applications.
HyperPose is a library for building high-performance custom pose estimation applications.
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
Deep Learning and Logical Reasoning from Data and Knowledge
Logic Tensor Networks (LTN) Logic Tensor Network (LTN) is a neurosymbolic framework that supports querying, learning and reasoning with both rich data
graph-theoretic framework for robust pairwise data association
CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides
Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.
IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se
PyTorch wrapper for Taichi data-oriented class
Stannum PyTorch wrapper for Taichi data-oriented class PRs are welcomed, please see TODOs. Usage from stannum import Tin import torch data_oriented =
Build a better understanding of your data in PostgreSQL.
Data Fluent for PostgreSQL Build a better understanding of your data in PostgreSQL. The following shows an example report generated by this tool. It g
Piotr - IoT firmware emulation instrumentation for training and research
Piotr: Pythonic IoT exploitation and Research Introduction to Piotr Piotr is an emulation helper for Qemu that provides a convenient way to create, sh
[Preprint] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora
Python parser for DTED data.
DTED Parser This is a package written in pure python (with help from numpy) to parse and investigate Digital Terrain Elevation Data (DTED) files. This
A discord bot consuming Notion API to add, retrieve data to Notion databases.
Notion-DiscordBot A discord bot consuming Notion API to add and retrieve data from Notion databases. Instructions to use the bot: Pre-Requisites: a)In
WAGMA-SGD is a decentralized asynchronous SGD for distributed deep learning training based on model averaging.
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.
Bagua is a flexible and performant distributed training algorithm development framework.
Bagua is a flexible and performant distributed training algorithm development framework.
Heimdall watchtower automatically sends you emails to notify you of the latest progress of your deep learning programs.
This software automatically sends you emails to notify you of the latest progress of your deep learning programs.
Spectral Tensor Train Parameterization of Deep Learning Layers
Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.
Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you
Check the basic quality of any dataset
Data Quality Checker in Python Check the basic quality of any dataset. Sneak Peek Read full tutorial at Medium. Explore the app Requirements python 3.
Data derived from the OpenType specification
This package currently provides the opentypespec.tags module, which exports FEATURE_TAGS, SCRIPT_TAGS, LANGUAGE_TAGS and BASELINE_TAGS dictionaries, representing data from the Layout Tag Registry
Yata is a fast, simple and easy Data Visulaization tool, running on python dash
Yata is a fast, simple and easy Data Visulaization tool, running on python dash. The main goal of Yata is to provide a easy way for persons with little programming knowledge to visualize their data easily.
Datargsing is a data management and manipulation Python library
Datargsing What is It? Datargsing is a data management and manipulation Python library which is currently in deving Why this library is good? This Pyt
Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.
Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.
mlscraper: Scrape data from HTML pages automatically with Machine Learning
🤖 Scrape data from HTML websites automatically with Machine Learning
Code for the paper "Balancing Training for Multilingual Neural Machine Translation, ACL 2020"
Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat
Distributed DataLoader For Pytorch Based On Ray
Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂,CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在,这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C
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
Shared code for training sentence embeddings with Flax / JAX
flax-sentence-embeddings This repository will be used to share code for the Flax / JAX community event to train sentence embeddings on 1B+ training pa
This is a simple backtesting framework to help you test your crypto currency trading. It includes a way to download and store historical crypto data and to execute a trading strategy.
You can use this simple crypto backtesting script to ensure your trading strategy is successful Minimal setup required and works well with static TP a
Source code for the paper "PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction" in ACL2021
PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20
Code implementation of Data Efficient Stagewise Knowledge Distillation paper.
Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image
This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code for training a DPR model then continuing training with RAG.
KGI (Knowledge Graph Induction) for slot filling This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code fo
Official code of paper "PGT: A Progressive Method for Training Models on Long Videos" on CVPR2021
PGT Code for paper PGT: A Progressive Method for Training Models on Long Videos. Install Run pip install -r requirements.txt. Run python setup.py buil
This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations at CVPR'21. According to some product reasons, we are not planning to release the training/testing codes and models. However, we will release the dataset and the scripts to prepare the dataset.
TransFill-Reference-Inpainting This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transf
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.
XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang
Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code
Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather than invoking the Python interpreter, Tuplex generates optimized LLVM bytecode for the given pipeline and input data set.
A Bot To Get Info Of Telegram messages , Media , Channel id Group ID etc.
Info-Bot A Bot To Get Info Of Telegram messages , Media , Channel id Group ID etc. Get Info Of Your And Messages , Channels , Groups ETC... How to mak
An advanced real time threat intelligence framework to identify threats and malicious web traffic on the basis of IP reputation and historical data.
ARTIF is a new advanced real time threat intelligence framework built that adds another abstraction layer on the top of MISP to identify threats and malicious web traffic on the basis of IP reputation and historical data. It also performs automatic enrichment and threat scoring by collecting, processing and correlating observables based on different factors.
The source codes for ACL 2021 paper 'BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data'
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for
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.
YoloV5 implemented by TensorFlow2 , with support for training, evaluation and inference.
Efficient implementation of YOLOV5 in TensorFlow2