5023 Repositories
Python Dimension-Reduced-Turbulent-Flow-Data-From-Deep-Vector-Quantizers Libraries
Gathers data and displays metrics related to climate change and resource depletion on a PowerBI report.
Apocalypse Status Dashboard Purpose Climate change and resource depletion are grave long-term dangers. The code in this repository will pull data from
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder
A rough implementation of the paper "A Steering Algorithm for Redirected Walking Using Reinforcement Learning"
A rough implementation of the paper "A Steering Algorithm for Redirected Walking Using Reinforcement Learning"
SPTAG: A library for fast approximate nearest neighbor search
SPTAG: A library for fast approximate nearest neighbor search SPTAG SPTAG (Space Partition Tree And Graph) is a library for large scale vector approxi
MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc.
MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc. ⭐⭐⭐⭐⭐
Compilation of resources and insights that helped me on my journey to data scientist
Compilation of resources and insights that helped me on my journey to data scientist
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
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
This is Assignment1 code for the Web Data Processing System.
This is a Python program to Entity Linking by processing WARC files. We recognize entities from web pages and link them to a Knowledge Base(Wikidata).
Numbering permanent and deciduous teeth via deep instance segmentation in panoramic X-rays
Numbering permanent and deciduous teeth via deep instance segmentation in panoramic X-rays In this repo, you will find the instructions on how to requ
Deep Image Matting implementation in PyTorch
Deep Image Matting Deep Image Matting paper implementation in PyTorch. Differences "fc6" is dropped. Indices pooling. "fc6" is clumpy, over 100 millio
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 Natural Image Matting via Guided Contextual Attention
GCA-Matting: Natural Image Matting via Guided Contextual Attention The source codes and models of Natural Image Matting via Guided Contextual Attentio
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
Bridging Composite and Real: Towards End-to-end Deep Image Matting
Bridging Composite and Real: Towards End-to-end Deep Image Matting Please note that the official repository of the paper Bridging Composite and Real:
Deep Video Matting via Spatio-Temporal Alignment and Aggregation [CVPR2021]
Deep Video Matting via Spatio-Temporal Alignment and Aggregation [CVPR2021] Paper: https://arxiv.org/abs/2104.11208 Introduction Despite the significa
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
The official repository for Deep Image Matting with Flexible Guidance Input
FGI-Matting The official repository for Deep Image Matting with Flexible Guidance Input. Paper: https://arxiv.org/abs/2110.10898 Requirements easydict
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
Minimum Bounding Box of Geospatial data
BBOX Problem definition: The spatial data users often are required to obtain the coordinates of the minimum bounding box of vector and raster data in
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.
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
Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).
PandasVault — Advanced Pandas Functions and Code Snippets The only Pandas utility package you would ever need. It has no exotic external dependencies
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
Automatically visualize your pandas dataframe via a single print! 📊 💡
A Python API for Intelligent Visual Discovery Lux is a Python library that facilitate fast and easy data exploration by automating the visualization a
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
Finding project directories in Python (data science) projects, just like there R rprojroot and here packages
Find relative paths from a project root directory Finding project directories in Python (data science) projects, just like there R here and rprojroot
Intake is a lightweight package for finding, investigating, loading and disseminating data.
Intake: A general interface for loading data Intake is a lightweight set of tools for loading and sharing data in data science projects. Intake helps
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 columnar data container that can be compressed.
Unmaintained Package Notice Unfortunately, and due to lack of resources, the Blosc Development Team is unable to maintain this package anymore. During
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
Benchmarks for the Optimal Power Flow Problem
Power Grid Lib - Optimal Power Flow This benchmark library is curated and maintained by the IEEE PES Task Force on Benchmarks for Validation of Emergi
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
Metrics to evaluate quality and efficacy of synthetic datasets.
An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://
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.
A DSL for data-driven computational pipelines
"Dataflow variables are spectacularly expressive in concurrent programming" Henri E. Bal , Jennifer G. Steiner , Andrew S. Tanenbaum Quick overview Ne
Vector tile server for the Wildfire Predictive Services Unit
wps-tileserver Vector tile server for the Wildfire Predictive Services Unit Overview The intention of this project is to: provide tools to easily spin
Integrate bus data from a variety of sources (batch processing and real time processing).
Purpose: This is integrate bus data from a variety of sources such as: csv, json api, sensor data ... into Relational Database (batch processing and r
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
SpinalNet: Deep Neural Network with Gradual Input
SpinalNet: Deep Neural Network with Gradual Input This repository contains scripts for training different variations of the SpinalNet and its counterp
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
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).
Python script for diving image data to train test and val
dataset-division-to-train-val-test-python python script for dividing image data to train test and val If you have an image dataset in the following st
Data repo for one-among.us
Our Data Data repo for one-among.us File Structure Directory /people/userid/: Data for a specific person info.json5: Profile information page.md: Pr
Pydantic based mock data generation
This library offers powerful mock data generation capabilities for pydantic based models. It can also be used with other libraries that use pydantic as a foundation, for example SQLModel, Beanie and ormar.
Maze generator and solver with python
Procedural-Maze-Generator-Algorithms Check out my youtube channel : Auctux Ressources Thanks to Jamis Buck Book : Mazes for programmers Requirements P
Helping you manage your data science projects sanely.
PyDS CLI Helping you manage your data science projects sanely. Requirements Anaconda/Miniconda/Miniforge/Mambaforge (Mambaforge recommended!) git on y
Source files for the data lake demo video using the AWS TICKIT database
Data Lake Demo Source code for video demonstration detailed in the post, Building a Simple Data Lake on AWS . Build a simple data lake on AWS using a
The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"
MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi
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*
This repository contains part of the code used to make the images visible in the article "How does an AI Imagine the Universe?" published on Towards Data Science.
Generative Adversarial Network - Generating Universe This repository contains part of the code used to make the images visible in the article "How doe
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
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized C
Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.
Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw
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
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
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
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:
eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
Command line utilities for tabular data files This is a set of command line utilities for manipulating large tabular data files. Files of numeric and
Desafio proposto pela IGTI em seu bootcamp de Cloud Data Engineer
Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data.
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data. Then used Yahoo Finance to get the related stock data and displayed them in the form of charts.
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
An implementation for the ICCV 2021 paper Deep Permutation Equivariant Structure from Motion.
Deep Permutation Equivariant Structure from Motion Paper | Poster This repository contains an implementation for the ICCV 2021 paper Deep Permutation
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
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
🔊 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
Extension to fastai for volumetric medical data
FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari
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
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
Fast style transfer
faststyle Faststyle aims to provide an easy and modular interface to Image to Image problems based on feature loss. Install Making sure you have a wor
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.
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval.
DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske
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
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)
Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF
Project5 Data processing system
Project5-Data-processing-system User just needed to copy both these file to a folder and open Project5.py using cmd or using any python ide. It is to
Epidemiology analysis package
zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is
Explorative Data Analysis Guidelines
Explorative Data Analysis Get data into a usable format! Find out if the following predictive modeling phase will be successful! Combine everything in
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
Data imputations library to preprocess datasets with missing data
Impyute is a library of missing data imputation algorithms. This library was designed to be super lightweight, here's a sneak peak at what impyute can do.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex
dirty_cat is a Python module for machine-learning on dirty categorical variables.
dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.
Pypeln is a simple yet powerful Python library for creating concurrent data pipelines.
Pypeln Pypeln (pronounced as "pypeline") is a simple yet powerful Python library for creating concurrent data pipelines. Main Features Simple: Pypeln
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use
Dump Data from FTDI Serial Port to Binary File on MacOS
Dump Data from FTDI Serial Port to Binary File on MacOS
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re