2462 Repositories
Python low-resource-machine-translation Libraries
End-to-End Speech Processing Toolkit
ESPnet: end-to-end speech processing toolkit system/pytorch ver. 1.3.1 1.4.0 1.5.1 1.6.0 1.7.1 1.8.1 1.9.0 ubuntu20/python3.9/pip ubuntu20/python3.8/p
CPC-big and k-means clustering for zero-resource speech processing
The CPC-big model and k-means checkpoints used in Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing.
rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.
Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.
The code from the Machine Learning Bookcamp book and a free course based on the book
The code from the Machine Learning Bookcamp book and a free course based on the book
Code for SALT: Stackelberg Adversarial Regularization, EMNLP 2021.
SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R
We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.
Salary-Prediction-with-Machine-Learning 1. Business Problem Can a machine learning project be implemented to estimate the salaries of baseball players
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
use machine learning to recognize gesture on raspberrypi
Raspberrypi_Gesture-Recognition use machine learning to recognize gesture on raspberrypi 說明 利用 tensorflow lite 訓練手部辨識模型 分辨 "剪刀"、"石頭"、"布" 之手勢 再將訓練模型匯入
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Training Efficiency We show the training efficiency of our DSLP model b
Official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning (ICML 2021) published at International Conference on Machine Learning
About This repository the official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning. The config files contain the s
The project is an open-source and low-cost kit to get started with underactuated robotics.
Torque Limited Simple Pendulum Introduction The project is an open-source and low-cost kit to get started with underactuated robotics. The kit targets
Steal Files on a Windows Machine
File-Stealer Steal Files on a Windows Machine About This Script will steal certain Files on a Windows Machine and sends them to a FTP Server. Preview
Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating
NLP, Machine learning
Netflix-recommendation-system NLP, Machine learning About Recommendation algorithms are at the core of the Netflix product. It provides their members
Painting app using Python machine learning and vision technology.
AI Painting App We are making an app that will track our hand and helps us to draw from that. We will be using the advance knowledge of Machine Learni
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
object recognition with machine learning on Respberry pi
Respberrypi_object-recognition object recognition with machine learning on Respberry pi line.py 建立一支與樹梅派連線的 linebot 使用此 linebot 遠端控制樹梅派拍照 config.ini l
CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning applications.
SmartSim Example Zoo This repository contains CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning appl
A style-based Quantum Generative Adversarial Network
Style-qGAN A style based Quantum Generative Adversarial Network (style-qGAN) model for Monte Carlo event generation. Tutorial We have prepared a noteb
SoGCN: Second-Order Graph Convolutional Networks
SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Training Efficiency We show the training efficiency of our DSLP model b
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
Youtube Downloader is a Graphic User Interface(GUI) that lets users download a Youtube Video or Audio through a URL
Youtube Downloader This Python and Tkinter based GUI allows users to directly download the Best Resolution Videos and Audios from Youtube. Pa-fy Insta
Bittensor - an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence
At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a
CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation
CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation We propose a novel approach to translate unpaired contrast computed
A cross-lingual COVID-19 fake news dataset
CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,
Breaking the Dilemma of Medical Image-to-image Translation
Breaking the Dilemma of Medical Image-to-image Translation Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that dominate the field
Breaking the Dilemma of Medical Image-to-image Translation
Breaking the Dilemma of Medical Image-to-image Translation Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that dominate the field
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.
mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do
A PyTorch implementation of paper "Learning Shared Semantic Space for Speech-to-Text Translation", ACL (Findings) 2021
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant
African language Speech Recognition - Speech-to-Text
Swahili-Speech-To-Text Table of Contents Swahili-Speech-To-Text Overview Scenario Approach Project Structure data: models: notebooks: scripts tests: l
A collection of learning outcomes data analysis using Python and SQL, from DQLab.
Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu
Additional tools for particle accelerator data analysis and machine information
PyLHC Tools This package is a collection of useful scripts and tools for the Optics Measurements and Corrections group (OMC) at CERN. Documentation Au
An end-to-end regression problem of predicting the price of properties in Bangalore.
Bangalore-House-Price-Prediction An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.
An addon uses SMPL's poses and global translation to drive cartoon character in Blender.
Blender addon for driving character The addon drives the cartoon character by passing SMPL's poses and global translation into model's armature in Ble
This repository is for EMNLP 2021 paper: It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data
InterpretationData This repository is for our EMNLP 2021 paper: It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpr
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.
Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra
A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering.
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
Dual Adaptive Sampling for Machine Learning Interatomic potential.
DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l
Uses WiFi signals :signal_strength: and machine learning to predict where you are
Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
Tribuo - A Java machine learning library
Tribuo - A Java prediction library (v4.1) Tribuo is a machine learning library in Java that provides multi-class classification, regression, clusterin
A game theoretic approach to explain the output of any machine learning model.
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
Machine Learning Algorithms
Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p
A Python script to capture images from multiple webcams at once and save them into your local machine
Capturing multiple images at once from Webcam Using OpenCV Capture multiple image by accessing the webcam of your system and save it to your machine.
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.
Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression
Some useful blender add-ons for SMPL skeleton's poses and global translation.
Blender add-ons for SMPL skeleton's poses and trans There are two blender add-ons for SMPL skeleton's poses and trans.The first is for making an offli
Build a translation program similar to Google Translate with Python programming language and QT library
google-translate Build a translation program similar to Google Translate with Python programming language and QT library Different parts of the progra
using Machine Learning Algorithm to classification AppleStore application
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
Graphsignal is a machine learning model monitoring platform.
Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model performance and availability.
This is a public repo where code samples are stored for the book Practical MLOps.
[Book-2021] Practical MLOps O'Reilly Book
XManager: A framework for managing machine learning experiments 🧑🔬
XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction with experiments is done via XManager's APIs through Python launch scripts.
Inykcal is a software written in python for selected E-Paper displays.
Inykcal is a software written in python for selected E-Paper displays. It converts these displays into useful information dashboards. It's open-source, free for personal use, fully modular and user-friendly. Despite all this, Inkycal can run well even on the Raspberry Pi Zero W. Oh, and it's open for third-party modules! Hooray!
Eland is a Python Elasticsearch client for exploring and analyzing data in Elasticsearch with a familiar Pandas-compatible API.
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
A Python library for choreographing your machine learning research.
A Python library for choreographing your machine learning research.
Dynamic Realtime Animation Control
Our project is targeted at making an application that dynamically detects the user’s expressions and gestures and projects it onto an animation software which then renders a 2D/3D animation realtime that gets broadcasted live.
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.
customer churn prediction prevention in telecom industry using machine learning and survival analysis
Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Make your master artistic punk avatar through machine learning world famous paintings
Master-art-punk Make your master artistic punk avatar through machine learning world famous paintings. 通过机器学习世界名画制作属于你的大师级艺术朋克头像 Nowadays, NFT is beco
2021 Machine Learning Security Evasion Competition
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
The first public PyTorch implementation of Attentive Recurrent Comparators
arc-pytorch PyTorch implementation of Attentive Recurrent Comparators by Shyam et al. A blog explaining Attentive Recurrent Comparators Visualizing At
Bald-to-Hairy Translation Using CycleGAN
GANiry: Bald-to-Hairy Translation Using CycleGAN Official PyTorch implementation of GANiry. GANiry: Bald-to-Hairy Translation Using CycleGAN, Fidan Sa
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. This library provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other libraries.
Resource hub for Obsidian resources.
Obsidian Community Vault Welcome! This is an experimental vault that is maintained by the Obsidian community. For best results we recommend downloadin
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd
Transfer-Learn is an open-source and well-documented library for Transfer Learning.
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Rhythm-Finder is a unsupervised ML driven python powered web-application that can find the songs that suits you.
ML-powered Music Recommendation Engine
Control System Packer is a lightweight, low-level program to transform energy equations into the compact libraries for control systems.
Control System Packer is a lightweight, low-level program to transform energy equations into the compact libraries for control systems. Packer supports Python 🐍 , C 💻 and C++ 💻 libraries.
A curated (most recent) list of resources for Learning with Noisy Labels
A curated (most recent) list of resources for Learning with Noisy Labels
Code repo for EMNLP21 paper "Zero-Shot Information Extraction as a Unified Text-to-Triple Translation"
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation Source code repo for paper Zero-Shot Information Extraction as a Unified Text
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their
The Ultimate FREE Machine Learning Study Plan
The Ultimate FREE Machine Learning Study Plan
A comprehensive repository containing 30+ notebooks on learning machine learning!
A comprehensive repository containing 30+ notebooks on learning machine learning!
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models tabular data.
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more
Machine learning template for projects based on sklearn library.
Machine learning template for projects based on sklearn library.
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition Currently
Some example scripts on pytorch
pytorch-practice Some example scripts on pytorch CONLL 2000 Chunking task Uses BiLSTM CRF loss with char CNN embeddings. To run use: cd data/conll2000
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P
PyTorch tutorials and best practices.
Effective PyTorch Table of Contents Part I: PyTorch Fundamentals PyTorch basics Encapsulate your model with Modules Broadcasting the good and the ugly
Minimal tutorials for PyTorch
Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials. Tensor multiplication Linear Regression Logistic Regression Neural Network
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone OS (Compiler)\LibTorch 1.9.0 macOS (clang 10.0, 11.0, 12.0) Linux (gcc 8, 9, 10, 11) Windows (msv
Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.
Deep Learning Materials by Deep Learning Wizard Start Learning Now Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet fr
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.
D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Book website | STAT 157 Course at UC Berkeley | Latest version
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic
Implementation of linear CorEx and temporal CorEx.
Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx