5671 Repositories
Python FastAPI-Learning-Example Libraries
Data loaders and abstractions for text and NLP
torchtext This repository consists of: torchtext.datasets: The raw text iterators for common NLP datasets torchtext.data: Some basic NLP building bloc
Datasets, Transforms and Models specific to Computer Vision
torchvision The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. Installat
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
fastFM: A Library for Factorization Machines
Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat
High performance implementation of Extreme Learning Machines (fast randomized neural networks).
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Extreme Learning Machine implementation in Python
Python-ELM v0.3 --- ARCHIVED March 2021 --- This is an implementation of the Extreme Learning Machine [1][2] in Python, based on scikit-learn. From
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
Python-based implementations of algorithms for learning on imbalanced data.
ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla
Python package for stacking (machine learning technique)
vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa
Library for machine learning stacking generalization.
stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab
Stacked Generalization (Ensemble Learning)
Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
Automated Machine Learning with scikit-learn
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Uplift modeling and causal inference with machine learning algorithms
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
[HELP REQUESTED] Generalized Additive Models in Python
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
Metric learning algorithms in Python
metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met
Simple structured learning framework for python
PyStruct PyStruct aims at being an easy-to-use structured learning and prediction library. Currently it implements only max-margin methods and a perce
Sequence learning toolkit for Python
seqlearn seqlearn is a sequence classification toolkit for Python. It is designed to extend scikit-learn and offer as similar as possible an API. Comp
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
Machine Learning toolbox for Humans
Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
A library of extension and helper modules for Python's data analysis and machine learning libraries.
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
A toolkit for making real world machine learning and data analysis applications in C++
dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl
mlpack: a scalable C++ machine learning library --
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
PySpark + Scikit-learn = Sparkit-learn
Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear
A modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
cuML - RAPIDS Machine Learning Library
cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
Generic template to bootstrap your PyTorch project with PyTorch Lightning, Hydra, W&B, and DVC.
NN Template Generic template to bootstrap your PyTorch project. Click on Use this Template and avoid writing boilerplate code for: PyTorch Lightning,
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a
Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch
Omninet - Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be atte
Qwerkey is a social media platform for connecting and learning more about mechanical keyboards built on React and Redux in the frontend and Flask in the backend on top of a PostgreSQL database.
Flask React Project This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github
Pneumonia Detection using machine learning - with PyTorch
Pneumonia Detection Pneumonia Detection using machine learning. Training was done in colab: DEMO: Result (Confusion Matrix): Data I uploaded my datase
D2Go is a toolkit for efficient deep learning
D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This
Deep Illuminator is a data augmentation tool designed for image relighting.
Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently genera
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
Dense Contrastive Learning (DenseCL) for self-supervised representation learning, CVPR 2021.
Dense Contrastive Learning for Self-Supervised Visual Pre-Training This project hosts the code for implementing the DenseCL algorithm for se
A framework for implementing federated learning
This is partly the reproduction of the paper of [Privacy-Preserving Federated Learning in Fog Computing](DOI: 10.1109/JIOT.2020.2987958. 2020)
An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)
GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
RELATE is an Environment for Learning And TEaching
RELATE Relate is an Environment for Learning And TEaching RELATE is a web-based courseware package. It is set apart by the following features: Focus o
Mnemosyne: efficient learning with powerful digital flash-cards.
Mnemosyne: Optimized Flashcards and Research Project Mnemosyne is: a free, open-source, spaced-repetition flashcard program that helps you learn as ef
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python library that helps data scientists to infer causation rather than observing correlation.
Open source platform for the machine learning lifecycle
MLflow: A Machine Learning Lifecycle Platform MLflow is a platform to streamline machine learning development, including tracking experiments, packagi
🦉Data Version Control | Git for Data & Models
Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci
a lightweight web framework based on fastapi
start-fastapi Version 2021, based on FastAPI, an easy-to-use web app developed upon Starlette Framework Version 2020 中文文档 Requirements python 3.6+ (fo
sample web application built with FastAPI + uvicorn
SPARKY Sample web application built with FastAPI & Python 3.8 shows simple Flask-like structure with a Bootstrap template index.html also has a backgr
Social Distancing Detector using deep learning and capable to run on edge AI devices such as NVIDIA Jetson, Google Coral, and more.
Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent
A rate limiter for Starlette and FastAPI
SlowApi A rate limiting library for Starlette and FastAPI adapted from flask-limiter. Note: this is alpha quality code still, the API may change, and
Example of integrating Poetry with Docker leveraging multi-stage builds.
Poetry managed Python FastAPI application with Docker multi-stage builds This repo serves as a minimal reference on setting up docker multi-stage buil
TODO aplication made with Python's FastAPI framework and Hexagonal Architecture
FastAPI Todolist Description Todolist aplication made with Python's FastAPI framework and Hexagonal Architecture. This is a test repository for the pu
📦 Autowiring dependency injection container for python 3
Lagom - Dependency injection container What Lagom is a dependency injection container designed to give you "just enough" help with building your depen
Admin Panel for GinoORM - ready to up & run (just add your models)
Gino-Admin Docs (state: in process): Gino-Admin docs Play with Demo (current master 0.2.3) Gino-Admin demo (login: admin, pass: 1234) Admin
更新 2.0 版本,使用 Python WEB 高性能异步框架 FastAPI 制作的抖音无水印解析下载,采用前后端分离思想!
前言 这个是 2.0 版本,使用现在流行的前后端分离思想重构。 体验网址:https://douyin.bigdataboy.cn 更新日志 2020.05.30:使用 FastAPI 前后端分离重构 2020.05.02:已更新,正常使用 2020.04.27:抖音结构更新,已修复视频有水印。(失
api versioning for fastapi web applications
fastapi-versioning api versioning for fastapi web applications Installation pip install fastapi-versioning Examples from fastapi import FastAPI from f
Reusable utilities for FastAPI
Reusable utilities for FastAPI Documentation: https://fastapi-utils.davidmontague.xyz Source Code: https://github.com/dmontagu/fastapi-utils FastAPI i
Ready-to-use and customizable users management for FastAPI
FastAPI Users Ready-to-use and customizable users management for FastAPI Documentation: https://frankie567.github.io/fastapi-users/ Source Code: https
The template for building scalable web APIs based on FastAPI, Tortoise ORM and other.
FastAPI and Tortoise ORM. Powerful but simple template for web APIs w/ FastAPI (as web framework) and Tortoise-ORM (for working via database without h
python fastapi example connection to mysql
Quickstart Then run the following commands to bootstrap your environment with poetry: git clone https://github.com/xiaozl/fastapi-realworld-example-ap
FastAPI framework plugins
Plugins for FastAPI framework, high performance, easy to learn, fast to code, ready for production fastapi-plugins FastAPI framework plugins Cache Mem
row level security for FastAPI framework
Row Level Permissions for FastAPI While trying out the excellent FastApi framework there was one peace missing for me: an easy, declarative way to def
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
JSON-RPC server based on fastapi
Description JSON-RPC server based on fastapi: https://fastapi.tiangolo.com Motivation Autogenerated OpenAPI and Swagger (thanks to fastapi) for JSON-R
官方文档已经有翻译的人在做了,
FastAPI 框架,高性能,易学,快速编码,随时可供生产 文档:https://fastapi.tiangolo.com 源码:https://github.com/tiangolo/fastapi FastAPI 是一个现代、快速(高性能)的 Web 框架,基于标准 Python 类型提示,使用
fastapi-crud-sync
Developing and Testing an API with FastAPI and Pytest Syncronous Example Want to use this project? Build the images and run the containers: $ docker-c
A simple docker-compose app for orchestrating a fastapi application, a celery queue with rabbitmq(broker) and redis(backend)
fastapi - celery - rabbitmq - redis - Docker A simple docker-compose app for orchestrating a fastapi application, a celery queue with rabbitmq(broker
Minimal example utilizing fastapi and celery with RabbitMQ for task queue, Redis for celery backend and flower for monitoring the celery tasks.
FastAPI with Celery Minimal example utilizing FastAPI and Celery with RabbitMQ for task queue, Redis for Celery backend and flower for monitoring the
FastAPI Boilerplate
FastAPI Boilerplate Features SQlAlchemy session Custom user class Top-level dependency Dependencies for specific permissions Celery SQLAlchemy for asy
Auth for use with FastAPI
FastAPI Auth Pluggable auth for use with FastAPI Supports OAuth2 Password Flow Uses JWT access and refresh tokens 100% mypy and test coverage Supports
FastAPI Admin Dashboard based on FastAPI and Tortoise ORM.
FastAPI ADMIN 中文文档 Introduction FastAPI-Admin is a admin dashboard based on fastapi and tortoise-orm. FastAPI-Admin provide crud feature out-of-the-bo
FastAPI + Django experiment
django-fastapi-example This is an experiment to demonstrate one potential way of running FastAPI with Django. It won't be actively maintained. If you'
FastAPI on Google Cloud Run
cloudrun-fastapi Boilerplate for running FastAPI on Google Cloud Run with Google Cloud Build for deployment. For all documentation visit the docs fold
Backend Skeleton using FastAPI and Sqlalchemy ORM
Backend API Skeleton Based on @tiangolo's full stack postgres template, with some things added, some things removed, and some things changed. This is
Backend, modern REST API for obtaining match and odds data crawled from multiple sites. Using FastAPI, MongoDB as database, Motor as async MongoDB client, Scrapy as crawler and Docker.
Introduction Apiestas is a project composed of a backend powered by the awesome framework FastAPI and a crawler powered by Scrapy. This project has fo
🤪 FastAPI + Vue构建的Mall项目后台管理
Mall项目后台管理 前段时间学习Vue写了一个移动端项目 https://www.charmcode.cn/app/mall/home 然后教程到此就结束了, 我就总感觉少点什么,计划自己着手写一套后台管理。 相关项目 移动端Mall项目源码(Vue构建): https://github.com/
FastAPI Learning Example,对应中文视频学习教程:https://space.bilibili.com/396891097
视频教学地址 中文学习教程 1、本教程每一个案例都可以独立跑,前提是安装好依赖包。 2、本教程并未按照官方教程顺序,而是按照实际使用顺序编排。 Video Teaching Address FastAPI Learning Example 1.Each case in this tutorial c
Example app using FastAPI and JWT
FastAPI-Auth Example app using FastAPI and JWT virtualenv -p python3 venv source venv/bin/activate pip3 install -r requirements.txt mv config.yaml.exa
[rewrite 중] 코로나바이러스감염증-19(COVID-19)의 국내/국외 발생 동향 조회 API | Coronavirus Infectious Disease-19 (COVID-19) outbreak trend inquiry API
COVID-19API 코로나 바이러스 감염증-19(COVID-19, SARS-CoV-2)의 국내/외 발생 동향 조회 API Corona Virus Infectious Disease-19 (COVID-19, SARS-CoV-2) outbreak trend inquiry
Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis https://arxiv.org/abs/2011.13775
CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi
Implements Gradient Centralization and allows it to use as a Python package in TensorFlow
Gradient Centralization TensorFlow This Python package implements Gradient Centralization in TensorFlow, a simple and effective optimization technique
Few-shot Learning of GPT-3
Few-shot Learning With Language Models This is a codebase to perform few-shot "in-context" learning using language models similar to the GPT-3 paper.
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"
Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo
3D Vision functions with end-to-end support for deep learning developers, written in Ivy.
Ivy vision focuses predominantly on 3D vision, with functions for camera geometry, image projections, co-ordinate frame transformations, forward warping, inverse warping, optical flow, depth triangulation, voxel grids, point clouds, signed distance functions, and others. Check out the docs for more info!
A demo of Prometheus+Grafana for monitoring an ML model served with FastAPI.
ml-monitoring Jeremy Jordan This repository provides an example setup for monitoring an ML system deployed on Kubernetes.
DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos.
DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos A concise deep reinforcement learning libr
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).
Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre