Python Machine-vision Resources

NoPdb: Non-interactive Python Debugger Installation: pip install nopdb Docs: https://nopdb.readthedocs.io/ NoPdb is a programmatic (non-interactive) d

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer

Welcome to MedicalTorch MedicalTorch is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets fo

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

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe

Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki

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).

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

Keyword: Speech Translation, Spoken Language Processing, Natural Language Processing

Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran

The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for experiments, and there is also QGAN (Quantum Generative Adversarial Network) algorithm.

FasySeq FasySeq is a shorthand as a Fast and easy sequential modeling toolkit. It aims to provide a seq2seq model to researchers and developers, which

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Involution: Inverting the Inherence of Convolution for Visual Recognition Unofficial PyTorch reimplementation of the paper Involution: Inverting the I

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.

bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies

Trading Using Q-Learning In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework

Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th

Algorithmic Trading This machine learning algorithm was built using Python 3 and scikit-learn with a Decision Tree Classifier. The program gathers sto

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Advances in Financial Machine Learning Exercises Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by

Documentation | Documentation (dev version) | Contact | Part of the Fatiando a Terra project About Verde is a Python library for processing spatial da

mahotas-imread: Read Image Files IO with images and numpy arrays. Mahotas-imread is a simple module with a small number of functions: imread Reads an

Mahotas Python Computer Vision Library Mahotas is a library of fast computer vision algorithms (all implemented in C++ for speed) operating over numpy

Automatic neural network visualizations generated in your browser!

Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis This is a PyTorch implementation of the Deep Streaming Linear Discriminant

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

💯 Days of Machine Learning and Deep Learning Code MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Cluste

ViViT: A Video Vision Transformer Unofficial implementation of ViViT: A Video Vision Transformer. Notes: This is in WIP. Model 2 is implemented, Model

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021) This repo presents PyTorch implementation of M

A Python Library for Document Layout Understanding

DeepViT This repo is the official implementation of "DeepViT: Towards Deeper Vision Transformer". The repo is based on the timm library (https://githu

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

emb-ntua-workshop This workshop discusses introductory concepts of machine learning and data mining following a hands-on approach using popular tools

Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w

Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in

ConViT : Vision Transformers with Convolutional Inductive Biases This repository contains PyTorch code for ConViT. It builds on code from the Data-Eff

Implementation of various Vision Transformers I found interesting

Machine Learning Conference & Summer School Notes. 🦄📝🎉

NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video Project Page | Paper NeuralRecon: Real-Time Coherent 3D Reconstruction from Mon

LoFTR: Detector-Free Local Feature Matching with Transformers Project Page | Paper LoFTR: Detector-Free Local Feature Matching with Transformers Jiami

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

A Study of Face Obfuscation in ImageNet Code for the paper: A Study of Face Obfuscation in ImageNet Kaiyu Yang, Jacqueline Yau, Li Fei-Fei, Jia Deng,

Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun

Code Transformer This is an official PyTorch implementation of the CodeTransformer model proposed in: D. Zügner, T. Kirschstein, M. Catasta, J. Leskov

The guide to tackle with the Text Summarization

Adversarial Training Against Location-Optimized Adversarial Patches arXiv | Paper | Code | Video | Slides Code for the paper: Sukrut Rao, David Stutz,

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

Rethinking Spatial Dimensions of Vision Transformers Byeongho Heo, Sangdoo Yun, Dongyoon Han, Sanghyuk Chun, Junsuk Choe, Seong Joon Oh | Paper NAVER

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

deep-significance: Easy and Better Significance Testing for Deep Neural Networks Contents ⁉️ Why 📥 Installation 🔖 Examples Intermezzo: Almost Stocha

Support Me 🚀 About Polaris 📄 Polaris is a system based on facial recognition with a futuristic GUI design, Can easily find people informations store

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl

skope-rules Skope-rules is a Python machine learning module built on top of scikit-learn and distributed under the 3-Clause BSD license. Skope-rules a

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

scikit-lego We love scikit learn but very often we find ourselves writing custom transformers, metrics and models. The goal of this project is to atte

combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla

Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l

Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

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

News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl

A lightweight, GPU accelerated, SQL engine built on the RAPIDS.ai ecosystem. Get Started on app.blazingsql.com Getting Started | Documentation | Examp

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Resources cuDF Reference Documentation: Python API refe

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn

Project Home Blog Documents Paper Media Coverage Join Fiber users email list [email protected] Fiber Distributed Computing for AI Made Simp

BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith

Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis