Python Learning-with-noisy-labels Resources

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye

Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie

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.

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

English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc

Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-

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

Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p

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 Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q

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...

A modular domain adaptation library written in PyTorch.

MSVCL_MICCAI2021 Installation Please follow the instruction in pytorch-CycleGAN-and-pix2pix to install. Example Usage An example of vendor-styles tran

Multi Camera Pig Tracking Official Implementation of Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras CVPR2021 CV4Animals Workshop P

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

MLJetReconstruction - using machine learning to reconstruct jets for CMS The C++ data extraction code used here was based heavily on that foundv here.

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Image Classification Dataset: Google Landmark, COCO, ImageNet Model: Efficient

CytoImageNet A large-scale pretraining dataset for bioimage transfer learning. Motivation In past few decades, the increase in speed of data collectio

cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear

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. Its objective is to ex

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the transforming parameters from data and then transform the data.

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut

Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and

stability-selection - A scikit-learn compatible implementation of stability selection stability-selection is a Python implementation of the stability

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv

WSDEC This is the official repo for our NeurIPS paper Weakly Supervised Dense Event Captioning in Videos. Description Repo directories ./: global conf

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place

tensorboardX Write TensorBoard events with simple function call. The current release (v2.3) is tested on anaconda3, with PyTorch 1.8.1 / torchvision 0

Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv

Katana project is a FastAPI template for ASAP 🚀 ML API deployment

GANSpace: Discovering Interpretable GAN Controls Figure 1: Sequences of image edits performed using control discovered with our method, applied to thr

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc

livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A

Bokeh-Python-Visualization A Bokeh project developed for learning and teaching Bokeh interactive plotting! See my medium blog posts about making bokeh

Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week

Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi

ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an

OpenMMLab FewShot Learning Toolbox and Benchmark

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst

Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li

AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

RecGURU About The Project Source code and baselines for the RecGURU paper "RecGURU: Adversarial Learning of Generalized User Representations for Cross

A Python library to create single or multi Instance-based Learning (IBL) agents that are built based on Instance Based Learning Theory (IBLT) 1 Instal

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

NFFT4ANOVA Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication" This package uses th

TransMorph: Transformer for Medical Image Registration keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registrati

UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Code Summary aggregate.py: this script aggr

The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme

ProxyFL Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing" Authors: Shivam Kalra*, Junfeng Wen*, Jess

Learning Versatile Neural Architectures by Propagating Network Codes Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang, Zhiwu Lu, Jingdong Wang,

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

Python-Fast-Raytracer A basic Ray Tracer that exploits numpy arrays and functions to work fast. The code is written keeping as much readability as pos

MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant

Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported

torchsynth The fastest synth in the universe. Introduction torchsynth is based upon traditional modular synthesis written in pytorch. It is GPU-option

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b

Barlow-Twins-TF This repository implements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrat

lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo

TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting

Convert Text-to Handwriting Using Python Description In this project we'll use python library that's "pywhatkit" for converting text to handwriting. t

Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,

Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are

Official Stanford NLP Python Library for Many Human Languages

Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P

Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C

AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Medical Open Network for AI MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem. Its am

FlexFlow FlexFlow is a deep learning framework that accelerates distributed DNN training by automatically searching for efficient parallelization stra

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition: