Python Failure-rate Resources

Website • Docs • Community Slack 💡 What is NannyML? NannyML is an open-source python library that allows you to estimate post-deployment model perfor

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 Rate limit semaphore for async-style (any core) There are t

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

Redis-based rate-limiting for FastAPI

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".

hh_ru_research Проект реализован в учебных целях анализа рынка труда, в особенности по hh.ru Input data В качестве входных данных используются сериали

Jigsaw Rate Severity of Toxic Comments

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.

ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple

This Notebook is based off an open source dataset available on where I have created models to classify patients who can potentially witness heart failure on the basis of various parameters. The best model had an accuracy of 94% and a recall of 91%

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.

FastAPIRateLimit Contributing is F&E (free&easy) Y Usage pip install farlimit N

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 Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p

Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c

Python EUR and USD rate parser. Python USD and EUR rate in RUB parser. Parsing i

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 aiohttp-ratelimiter is a rate limiter for the aiohttp.web fr

PRP Introduction This is the implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".

Characterizing possible failure modes in physics-informed neural networks This repository contains the PyTorch source code for the experiments in the

jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd

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

Throttler Zero-dependency Python package for easy throttling with asyncio support. 📝 Table of Contents 🎒 Install 🛠 Usage Examples Throttler and Thr

Automated Learning Rate Scheduler for Large-Batch Training The official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th

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 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 This repository contains an implementation of AdamW optimization algorithm and cosine

Learning-Rate-Dropout Pytorch implementation of Learning Rate Dropout. Paper Link: https://arxiv.org/pdf/1912.00144.pdf Train ResNet-34 for Cifar10: r

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

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

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar

GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N

CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme

DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph

Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform This repository is the implementation of "Variable-Rate Deep Image C

DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a

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

LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.

A FastAPI Framework for things like Database, Redis, Logging, JWT Authentication and Rate Limits Install You can install this Library with: pip instal

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, 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).

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

robotframework-stacktrace A listener for RF = 4.0 that prints a Stack Trace to console to faster find the code section where the failure appears. Ins

Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)

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-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu

Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl

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

Tenacity Tenacity is an Apache 2.0 licensed general-purpose retrying library, written in Python, to simplify the task of adding retry behavior to just

Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner This repository is the official implementation of Meta-rPPG: Remote Heart Ra

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

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

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

Tenacity Tenacity is an Apache 2.0 licensed general-purpose retrying library, written in Python, to simplify the task of adding retry behavior to just

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

fastapi-limiter Introduction FastAPI-Limiter is a rate limiting tool for fastapi routes. Requirements redis Install Just install from pypi pip insta

fastapi-limiter Introduction FastAPI-Limiter is a rate limiting tool for fastapi routes. Requirements redis Install Just install from pypi pip insta

Text progress bar library for Python. Travis status: Coverage: Install The package can be installed through pip (this is the recommended method): pip

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

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

Flask-Limiter Flask-Limiter provides rate limiting features to flask routes. It has support for a configurable backend for storage with current implem

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