Python Data-efficient-learning Resources

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

Self-supervised Graph-level Representation Learning with Local and Global Structure Introduction This project is an implementation of ``Self-supervise

CL-Gym: Full-Featured PyTorch Library for Continual Learning CL-Gym is a small yet very flexible library for continual learning research and developme

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

REDQ source code Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm. Paper link: https://arxiv.org/abs/2101.05

IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a

TS-CAM: Token Semantic Coupled Attention Map for Weakly SupervisedObject Localization This is the official implementaion of paper TS-CAM: Token Semant

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme

DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w

spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline

SPARSEDNN **If you want to use this repo, please send me an email: [email protected], or raise a Github issue. ** Fast sparse deep learning on CPUs

Stannum PyTorch wrapper for Taichi data-oriented class PRs are welcomed, please see TODOs. Usage from stannum import Tin import torch data_oriented =

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

Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora

Learning to See by Looking at Noise This is the official implementation of Learning to See by Looking at Noise. In this work, we investigate a suite o

Time Series Research with Torch 这个开源项目主要是对经典的时间序列预测算法论文进行复现，模型主要参考自GluonTS，框架主要参考自Informer。 建立原因 相较于mxnet和TF，Torch框架中的神经网络层需要提前指定输入维度： # 建立线性层 TensorF

Project page for the paper Semi-Supervised Raw-to-Raw Mapping 2021.

SWAL Code for Paper "Selective Wavelet Attention Learning for Single Image Deraining" Prerequisites Python 3 PyTorch Models We provide the models trai

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

MNIST on the Web An attempt to predict MNIST handwritten digits from my PyTorch model from the browser (client-side) and not from the server, with the

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 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.

MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives.

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 This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

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

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

Hangman game The Hangman game is a game whereby one person thinks of a word, which is kept secret from another person, who tries to guess the word one

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.

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

Posture: Pose Tracking and Machine Learning for prescribing corrective suggestions to improve posture and form while exercising. This repository conta

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 What is It? Datargsing is a data management and manipulation Python library which is currently in deving Why this library is good? This Pyt

imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

TensorRT examples (Jetson, Python/C++)(object detection)

Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.

🤖 Scrape data from HTML websites automatically with Machine Learning

2021-CVPR-MvCLN This repo contains the code and data of the following paper accepted by CVPR 2021 Partially View-aligned Representation Learning with

RSG: A Simple but Effective Module for Learning Imbalanced Datasets (CVPR 2021) A Pytorch implementation of our CVPR 2021 paper "RSG: A Simple but Eff

TS2Vec This repository contains the official implementation for the paper Learning Timestamp-Level Representations for Time Series with Hierarchical C

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

This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML). It can build custom modeling pipelines for different real-world processes in an automated way using an evolutionary approach. FEDOT supports classification (binary and multiclass), regression, clustering, and time series prediction tasks.

Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

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

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image

Learning Canonical Representations for Scene Graph to Image Generation (ECCV 2020) Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, A

RoseTTAFold This package contains deep learning models and related scripts to run RoseTTAFold This repository is the official implementation of RoseTT

CLCC: Contrastive Learning for Color Constancy (CVPR 2021) Yi-Chen Lo*, Chia-Che Chang*, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang,

ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea

LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequ

Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi

ShapeGlot: Learning Language for Shape Differentiation Created by Panos Achlioptas, Judy Fan, Robert X.D. Hawkins, Noah D. Goodman, Leonidas J. Guibas

LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow

Curious Representation Learning for Embodied Intelligence This is the pytorch code for the paper Curious Representation Learning for Embodied Intellig

Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape

XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

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.

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.

DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search

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

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.

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for

Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label

Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

seno-blockchain https://seno.uno Seno is just a fork of Chia, designed to be efficient, decentralized, and secure. Here are some of the features and b

Falken provides developers with a service that allows them to train AI that can play their games. Unlike traditional RL frameworks that learn through rewards or batches of offline training, Falken is based on training AI via realtime, human interactions.

A python library to build Model Trees with Linear Models at the leaves.

Extensive tutorials for learning how to build deep learning models for causal inference using selection on observables in Tensorflow 2.

A data preprocessing package for time series data. Design for machine learning and deep learning.

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

tinyGS-antenna-map This is the antenna performance plotted from tinyGS reception data. See their repository. The code produces a plot that provides Az

XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang

What is nnDetection? Simultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of hi

Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.

Scirpy: A Scanpy extension for analyzing single-cell immune-cell receptor sequencing data Scirpy is a scalable python-toolkit to analyse T cell recept

Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on

Shared Attention for Multi-label Zero-shot Learning Overview This repository contains the implementation of Shared Attention for Multi-label Zero-shot

CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6

Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns

SEDE SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their natural language description

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

Cross-Modal Contrastive Learning for Text-to-Image Generation This repository hosts the open source JAX implementation of XMC-GAN. Setup instructions

Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

rage-lint Lint RAGE (only GTA5 at the moment) meta/XML files for validity based off of the GTA5.xsd generated from game code. This script accepts a se

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch