Python Data-efficient-gan-training Resources

AWS Data Engineering Pipeline This is a repository for the Duke University Cloud Computing course project on Serverless Data Engineering Pipeline. For

Tamil Nadu Chief Minister's Relief Fund Donors Scrapped data from https://ereceipt.tn.gov.in/cmprf/Interface/CMPRF/MonthWiseReport Scrapper scrapper.p

train-CLIP 📎 A PyTorch Lightning solution to training CLIP from scratch. Goal ⚽ Our aim is to create an easy to use Lightning implementation of OpenA

iterable-subprocess Python utility function to communicate with a subprocess using iterables: for when data is too big to fit in memory and has to be

Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

A package to aggregate gridded data in xarray to polygons in geopandas using area-weighting from the relative area overlaps between pixels and polygons.

Graphsignal Logger Overview Graphsignal is an observability platform for monitoring and troubleshooting production machine learning applications. It h

Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback About This repository accompanies the real-world experiments conducted i

Python function to stream unzip all the files in a ZIP archive: without loading the entire ZIP file or any of its files into memory at once

Show Data is to generate html tables for large scale image dataset, especially for the dataset in remote server. It provides some useful commond line tools and fully customizeble API reference to generate html table different tasks.

Stream Framework Activity Streams & Newsfeeds Stream Framework is a Python library which allows you to build activity streams & newsfeeds using Cassan

tinkproject The program for portfolio analysis via Tinkoff API Hello! This is my first project, please, don't judge me. This project was developed for

Multi-Task Framework for Cross-Lingual Abstractive Summarization (MCLAS) The code for ACL2021 paper Cross-Lingual Abstractive Summarization with Limit

A curated list of programmatic weak supervision papers and resources

Deep learning toolbox based on PyTorch for hyperspectral data classification.

Code & Data for Enhancing Photorealism Enhancement

A framework for cleaning Chinese dialog data

MALib A general-purpose multi-agent training framework. Installation step1: build environment conda create -n malib python==3.7 -y conda activate mali

Esparto is a simple HTML and PDF document generator for Python. Its primary use is for generating shareable single page reports with content from popular analytics and data science libraries.

LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search The official implementation of the paper LightTra

👩‍✈️ Coqpit Simple, light-weight and no dependency config handling through python data classes with to/from JSON serialization/deserialization. Curre

GAN Memory for Lifelong learning This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting. Please consider citing our paper

This is the XLM-T repository, which includes data, code and pre-trained multilingual language models for Twitter. XLM-T - A Multilingual Language Mode

Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.

Hue Editor: Open source SQL Query Assistant for Databases/Warehouses

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar

torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions.

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

erdantic is a simple tool for drawing entity relationship diagrams (ERDs) for Python data model classes. Diagrams are rendered using the venerable Graphviz library.

AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data [WIP] Unofficial Pytorch implementation of AdaSpeech 2. Requirements : All code written i

CLEAR: Consistent Lifting, Embedding, and Alignment Rectification Algorithm The Matlab, Python, and C++ implementation of the CLEAR algorithm, as desc

HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F

LADA This repo contains codes for the following paper: Jiaao Chen*, Zhenghui Wang*, Ran Tian, Zichao Yang, Diyi Yang: Local Additivity Based Data Augm

Learning Representational Invariances for Data-Efficient Action Recognition Official PyTorch implementation for Learning Representational Invariances

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

django-import-export django-import-export is a Django application and library for importing and exporting data with included admin integration. Featur

ShapeInversion Paper Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, Chen Change Loy "Unsupervised 3D

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.

causaldata This repository will contain R, Stata, and Python packages, all called causaldata, which contain data sets that can be used to implement th

hyppo (HYPothesis Testing in PythOn, pronounced "Hippo") is an open-source software package for multivariate hypothesis testing.

Invert and perturb GAN images for test-time ensembling

Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe

GAN Ensembling Project Page | Paper | Bibtex Ensembling with Deep Generative Views. Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhan

RMNet This repository contains the source code for the paper Efficient Regional Memory Network for Video Object Segmentation. Cite this work @inprocee

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

MiVOS (CVPR 2021) - Mask Propagation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] [Papers with Code] This repo impleme

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

SharinGAN Official repo for the work titled "SharinGAN: Combining Synthetic and Real Data for Unsupervised GeometryEstimation" The official project we

TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and GPT) or huge classes (millions). It has the same API design as PyTorch.

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f

pihole-antitelemetry Research shows Google collects 20x more data from Android than Apple collects from iOS. Block both using these pihole lists. Proj

SARS-CoV-2 processing requests Request execution of Galaxy SARS-CoV-2 variation analysis workflows on input data you provide. Prerequisites This autom

FastAPI-Wrapper CLI & APIness Streamlit App Arvindra Sehmi, Oxford Economics Ltd. | Website | LinkedIn (Updated: 21 April, 2021) fastapi-wrapper is mo

collie_recs Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Coll

xarray-sentinel WARNING: this product is a "technology preview" / pre-Alpha Xarray backend to explore and load Copernicus Sentinel-1 satellite data pr

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

Fine-Grained R2R Code and data of the Fine-Grained R2R Dataset proposed in the EMNLP2020 paper Sub-Instruction Aware Vision-and-Language Navigation. C

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning (NeurIPS 2020) Introduction AdaShare is a novel and differentiable approach fo

Gender Bangs Body Side Pose (Yaw) Lighting Smile Face Shape Lipstick Color Painting Style Pose (Yaw) Pose (Pitch) Zoom & Rotate Flush & Eye Color Mout

🏅 Collection of Kaggle Solutions and Ideas 🏅

Cockpit is a visual and statistical debugger specifically designed for deep learning!

PlenOctrees Official Repo: NeRF-SH training and conversion This repository contains code to train NeRF-SH and to extract the PlenOctree, constituting

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.

ST3D Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 Authors: Jihan Yang*, Shaoshu

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

small python skript to display tradegate data on a waveshare e-ink important you need locale "de_AT.UTF-8 UTF-8" installed. do so in raspi-config's Lo

Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Dice Loss for NLP Tasks This repository contains code for Dice Loss for Data-imbalanced NLP Tasks at ACL2020. Setup Install Package Dependencies The c

Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels without pre-existing datasets. The only available option is often to collect and annotate texts by hand, which is expensive and time-consuming.

drawdata This small python app allows you to draw a dataset in a jupyter notebook. This should be very useful when teaching machine learning algorithm

ETL Pipeline with Airflow, Spark, s3, MongoDB and Amazon Redshift

Compact Transformers Preprint Link: Escaping the Big Data Paradigm with Compact Transformers By Ali Hassani[1]*, Steven Walton[1]*, Nikhil Shah[1], Ab

Simple but maybe too simple config management through python data classes. We use it for machine learning.

Generating Persona Consistent Dialogues by Exploiting Natural Language Inference Source code for RCDG model in AAAI20 Generating Persona Consistent Di

README Augment training images for deep neural networks by randomizing their visual style, as described in our paper: https://arxiv.org/abs/1809.05375

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

DECOR-GAN PyTorch 1.5 implementation for paper DECOR-GAN: 3D Shape Detailization by Conditional Refinement, Zhiqin Chen, Vladimir G. Kim, Matthew Fish

BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat

b3d_mocap_import addon for blender to import mocap data from tools like easymocap, frankmocap and Vibe ==================VIBE================== To use

The Django Leaflet Admin List package provides an admin list view featured by the map and bounding box filter for the geo-based data of the GeoDjango. It requires a django-leaflet package.

youtube-cdl Command line tool based on youtube-dl to easily download selected channels from your subscriptions. This tool is very handy if you want to

⚡ OPAL ⚡ Open Policy Administration Layer OPAL is an administration layer for Open Policy Agent (OPA), detecting changes to both policy and policy dat

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

DataTuner You have just found the DataTuner. This repository provides tools for fine-tuning language models for a task. See LICENSE.txt for license de

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

DABO: Data Augmentation with Bilevel Optimization [Paper] The goal is to automatically learn an efficient data augmentation regime for image classific