56 Repositories
Flutter rate-limiting Libraries
Audio-analytics for music-producers! Automate tedious tasks such as musical scale detection, BPM rate classification and audio file conversion.
Click here to be re-directed to the Beat Inspect Streamlit Web-App You are a music producer? Let's get in touch via LinkedIn Fundamental Analytics for
Rate-limit-semaphore - Semaphore implementation with rate limit restriction for async-style (any core)
Rate Limit Semaphore Rate limit semaphore for async-style (any core) There are t
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".
TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr
SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers
SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers This repo contains our codes for the paper "No Parameters Left Behind: Sensitivity Gu
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning"
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning".
A research of IT labor market based especially on hh.ru. Salaries, rate of technologies and etc.
hh_ru_research Проект реализован в учебных целях анализа рынка труда, в особенности по hh.ru Input data В качестве входных данных используются сериали
This project implements "virtual speed" from heart rate monito
ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple
Ab testing - The using AB test to test of difference of conversion rate
Facebook recently introduced a new type of offer that is an alternative to the current type of bidding called maximum bidding he introduced average bidding.
Farlimit - FastAPI rate limit with python
FastAPIRateLimit Contributing is F&E (free&easy) Y Usage pip install farlimit N
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
Python USD rate in RUB parser
Python EUR and USD rate parser. Python USD and EUR rate in RUB parser. Parsing i
Modified prey-predator system - Modified prey–predator model describes the rate of change for each species by adding coupling terms.
Modified prey-predator system We aim to study the behaviors of the modified prey–predator model and establish the effects of several parameters that p
aiohttp-ratelimiter is a rate limiter for the aiohttp.web framework.
aiohttp-ratelimiter aiohttp-ratelimiter is a rate limiter for the aiohttp.web fr
Implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
PRP Introduction This is the implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python
jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd
PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI).
PyBERT PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI). It uses the Traits/UI package of t
🔀⏳ Easy throttling with asyncio support
Throttler Zero-dependency Python package for easy throttling with asyncio support. 📝 Table of Contents 🎒 Install 🛠 Usage Examples Throttler and Thr
Official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th ICML Workshop on AutoML)
Automated Learning Rate Scheduler for Large-Batch Training The official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th
Automatic learning-rate scheduler
AutoLRS This is the PyTorch code implementation for the paper AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly published
Long Expressive Memory (LEM)
Long Expressive Memory for Sequence Modeling This repository contains the implementation to reproduce the numerical experiments of the paper Long Expr
AdamW optimizer and cosine learning rate annealing with restarts
AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine
Pytorch implementation of Learning Rate Dropout.
Learning-Rate-Dropout Pytorch implementation of Learning Rate Dropout. Paper Link: https://arxiv.org/pdf/1912.00144.pdf Train ResNet-34 for Cifar10: r
Block when attacker want to bypass the limit of request
Block when attacker want to bypass the limit of request
Epidemiology analysis package
zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is
Get informed when your DeFI Earn CRO Validator is jailed or changes the commission rate.
CRO-DeFi-Warner Intro CRO-DeFi-Warner can be used to notify you when a validator changes the commission rate or gets jailed. It can also notify you wh
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar
A Pytorch Implementation of a continuously rate adjustable learned image compression framework.
GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N
CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhancement
CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme
The implementation of the submitted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.
DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph
Official implementation of "Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform", ICCV 2021
Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform This repository is the implementation of "Variable-Rate Deep Image C
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).
DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a
On the Variance of the Adaptive Learning Rate and Beyond
RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte
A FastAPI Framework for things like Database, Redis, Logging, JWT Authentication and Rate Limits
A FastAPI Framework for things like Database, Redis, Logging, JWT Authentication and Rate Limits Install You can install this Library with: pip instal
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop a ecosystem to experiment, share, reproduce, and deploy in real world in a smooth and easy way (Hope it can be done).
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)
Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle
Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)
Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)
Package pyVHR is a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG)
Package pyVHR (short for Python framework for Virtual Heart Rate) is a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG)
PyTorch implementation of some learning rate schedulers for deep learning researcher.
pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu
PyTorch implementation of the paper Deep Networks from the Principle of Rate Reduction
Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl
API Rate Limit Decorator
ratelimit APIs are a very common way to interact with web services. As the need to consume data grows, so does the number of API calls necessary to re
Implementation of "Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner"
Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner This repository is the official implementation of Meta-rPPG: Remote Heart Ra
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
ASGI middleware for authentication, rate limiting, and building CRUD endpoints.
Piccolo API Utilities for easily exposing Piccolo models as REST endpoints in ASGI apps, such as Starlette and FastAPI. Includes a bunch of useful ASG
API Rate Limit Decorator
ratelimit APIs are a very common way to interact with web services. As the need to consume data grows, so does the number of API calls necessary to re
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
A request rate limiter for fastapi
fastapi-limiter Introduction FastAPI-Limiter is a rate limiting tool for fastapi routes. Requirements redis Install Just install from pypi pip insta
A request rate limiter for fastapi
fastapi-limiter Introduction FastAPI-Limiter is a rate limiting tool for fastapi routes. Requirements redis Install Just install from pypi pip insta
Progressbar 2 - A progress bar for Python 2 and Python 3 - "pip install progressbar2"
Text progress bar library for Python. Travis status: Coverage: Install The package can be installed through pip (this is the recommended method): pip
A Fast, Extensible Progress Bar for Python and CLI
tqdm tqdm derives from the Arabic word taqaddum (تقدّم) which can mean "progress," and is an abbreviation for "I love you so much" in Spanish (te quie
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
Rate Limiting extension for Flask
Flask-Limiter Flask-Limiter provides rate limiting features to flask routes. It has support for a configurable backend for storage with current implem
eyeD3 is a Python module and command line program for processing ID3 tags. Information about mp3 files (i.e bit rate, sample frequency, play time, etc.) is also provided. The formats supported are ID3v1 (1.0/1.1) and ID3v2 (2.3/2.4).
Status About eyeD3 is a Python tool for working with audio files, specifically MP3 files containing ID3 metadata (i.e. song info). It provides a comma