Python SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING Resources

ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn

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

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab

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. It provides the following features: Fast reading and distributed data preprocessing/cle

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

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 is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

PyStruct PyStruct aims at being an easy-to-use structured learning and prediction library. Currently it implements only max-margin methods and a perce

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

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

Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main

[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

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

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

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

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

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

NN Template Generic template to bootstrap your PyTorch project. Click on Use this Template and avoid writing boilerplate code for: PyTorch Lightning,

COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a

Omninet - Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be atte

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 Pneumonia Detection using machine learning. Training was done in colab: DEMO: Result (Confusion Matrix): Data I uploaded my datase

D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W

EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This

Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently genera

Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c

Dense Contrastive Learning for Self-Supervised Visual Pre-Training This project hosts the code for implementing the DenseCL algorithm for se

This is partly the reproduction of the paper of [Privacy-Preserving Federated Learning in Fog Computing](DOI: 10.1109/JIOT.2020.2987958. 2020)

An anthology of a variety of tools for the Persian language in Python

GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,

E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G

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 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: 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.

MLflow: A Machine Learning Lifecycle Platform MLflow is a platform to streamline machine learning development, including tracking experiments, packagi

Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci

Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent

FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre

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

CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi

Gradient Centralization TensorFlow This Python package implements Gradient Centralization in TensorFlow, a simple and effective optimization technique

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, 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.

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

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!

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 A concise deep reinforcement learning libr

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official

Roadmap to becoming a machine learning engineer in 2020, inspired by web-developer-roadmap.

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).

Gaphor Gaphor is a UML and SysML modeling application written in Python. It is designed to be easy to use, while still being powerful. Gaphor implemen

naked is a Python tool which allows you to strip a model and only keep what matters for making predictions. The result is a pure Python function with no third-party dependencies that you can simply copy/paste wherever you wish.

A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind

pre-commit-ci-config validation for pre-commit.ci configuration installation pip install pre-commit-ci-config api pre_commit_ci_config.SCHEMA a cfgv s

SSD: Single Shot MultiBox Detector Introduction Here is my pytorch implementation of 2 models: SSD-Resnet50 and SSDLite-MobilenetV2.

TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.

Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks. It takes raw videos/images + text as inputs, and outputs task predictions. ClipBERT is designed based on 2D CNNs and transformers, and uses a sparse sampling strategy to enable efficient end-to-end video-and-language learning.

Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals This repo contains the Pytorch implementation of our paper: Unsupervised Seman

hope-autonomous-driving Autonomous Driving project for Euro Truck Simulator 2 Video: How is it working ? In this video, the program processes the imag

ofxTensorFlow2 This is an openFrameworks addon for the TensorFlow 2 ML (Machine Learning) library

BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.

Rebiber: A tool for normalizing bibtex with official info. We often cite papers using their arXiv versions without noting that they are already PUBLIS

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.

HyperTag HyperTag helps humans intuitively express how they think about their files using tags and machine learning.

This is where I learn machine learning🤷‍ This means that this repo covers no specific topic of machine learning or a project - I work in here when I want to learn/try something

GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

MiniJVM MiniJVM是一款使用python编写的简易JVM，能够从本地加载class文件并且执行绝大多数指令。 支持的功能 1.从本地磁盘加载class并解析 2.支持绝大多数指令集的执行 3.支持虚拟机内存分区以及对象的创建 4.支持方法的调用和参数传递 5.支持静态代码块的初始化 不支

xgbse: XGBoost Survival Embeddings "There are two cultures in the use of statistical modeling to reach conclusions from data

Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch

Puzzle-CAM The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".

Multimodal Reinforcement Learning JAX implementations of the following multimodal reinforcement learning approaches. Dual-coding Episodic Memory from

This is a pre-commit hook configured to automatically upgrade your type hints to the new native types implemented in PEP 585.

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

HyperTag helps humans intuitively express how they think about their files using tags and machine learning. Represent how you think using tags. Find what you look for using semantic search for your text documents (yes, even PDF's) and images.

PyTorch实现多种计算机视觉中网络设计中用到的Attention机制，还收集了一些即插即用模块。由于能力有限精力有限，可能很多模块并没有包括进来，有任何的建议或者改进，可以提交issue或者进行PR。

Unbiased Teacher for Semi-Supervised Object Detection This is the PyTorch implementation of our paper: Unbiased Teacher for Semi-Supervised Object Detection

DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches the answers out of 60 billion phrases in Wikipedia, it is also very accurate having competitive accuracy with state-of-the-art open-domain QA models

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? when we can simply build a model with yaml markup file. Kindle builds a model with no code but yaml file which its method is inspired from YOLOv5.

Weakly Supervised Learning of Rigid 3D Scene Flow This repository provides code and data to train and evaluate a weakly supervised method for rigid 3D

pre-commit-dbt List of pre-commit hooks to ensure the quality of your dbt projects. BETA NOTICE: This tool is still BETA and may have some bugs, so pl

Supported tags and respective Dockerfile links python3.8, latest (Dockerfile) python3.7, (Dockerfile) python3.6 (Dockerfile) python3.8-slim (Dockerfil

cookiecutter-fastapi In order to create a template to FastAPI projects. 🚀 Important To use this project you don't need fork it. Just run cookiecutter

cookiecutter-spacy-fastapi Python cookiecutter API for quick deployments of spaCy models with FastAPI Azure Search The API interface is compatible wit

FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre

Official repo for QHack—the quantum machine learning hackathon