Python Performance-prediction Resources

SysInfo SysInfo is an app developed in python which gives Basic System Info , and some detailed graphs of system performance . Installation Download t

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

DownTime-Score DownTime-Score is a Small project aimed to Monitor the performance and the availabillity of a variety of the Vital and Critical Morocca

Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict

High-Performance Brain-to-Text Communication via Handwriting Overview This repo is associated with this manuscript, preprint and dataset. The code can

Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

TANL: Structured Prediction as Translation between Augmented Natural Languages Code for the paper "Structured Prediction as Translation between Augmen

Cinder is Instagram's internal performance-oriented production version of CPython 3.8. It contains a number of performance optimizations, including bytecode inline caching, eager evaluation of coroutines, a method-at-a-time JIT, and an experimental bytecode compiler that uses type annotations to emit type-specialized bytecode that performs better in the JIT.

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL-first e-commerce platform delivering ultra-fast, dynamic, personaliz

Django Cachalot Caches your Django ORM queries and automatically invalidates them. Documentation: http://django-cachalot.readthedocs.io Table of Conte

LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transformer, etc. It is therefore best useful for Machine Translation, Text Generation, Dialog， Language Modelling, and other related tasks using these models.

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction This is the code for the paper Combining E

AdelaiDepth is an open source toolbox for monocular depth prediction.

Structural basis for solubility in protein expression systems Large-scale protein production for biotechnology and biopharmaceutical applications rely

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

TalkNet 2 [WIP] TalkNet 2: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis with Explicit Pitch and Duration Predictio

Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

An easy-to-use high-performance asynchronous web framework.

Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.

bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

Welcome to Cython! Cython is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports mo

Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W

Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,

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

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures i

BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

empyrical Common financial risk metrics. Table of Contents Installation Usage Support Contributing Testing Installation pip install empyrical Usage S

WIMP - What If Motion Predictor Reference PyTorch Implementation for What If Motion Prediction [PDF] [Dynamic Visualizations] Setup Requirements The W

Feel free to visit my homepage Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DIMP) [ECCVW2020 paper] Presentation

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

LPC_for_TTS Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm. 基于Levinson-Durbin

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

whatthelang Lightning Fast Language Prediction 🚀 Dependencies The dependencies can be installed using the requirements.txt file: $ pip install -r req

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

Sequence -----------+-- 3D_structure -- 3D_module --+ +-- ? | |

TrajNet++ : The Trajectory Forecasting Framework PyTorch implementation of Human Trajectory Forecasting in Crowds: A Deep Learning Perspective TrajNet

FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.

What is EdgeDB? EdgeDB is an open-source object-relational database built on top of PostgreSQL. The goal of EdgeDB is to empower its users to build sa

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

datatable This is a Python package for manipulating 2-dimensional tabular data structures (aka data frames). It is close in spirit to pandas or SFrame

Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-

======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol

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

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

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

Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL-first e-commerce platform delivering ultra-fast, dynamic, personaliz

fastapi-gino-arq-uvicorn High-performance Async REST API, in Python. FastAPI + GINO + Arq + Uvicorn (powered by Redis & PostgreSQL). Contents Get Star

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

fastapi_profiler A FastAPI Middleware of joerick/pyinstrument to check your service performance. 📣 Info A FastAPI Middleware of pyinstrument to check

The DeepSparse Engine is a CPU runtime that delivers unprecedented performance by taking advantage of natural sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.

DISCONTINUATION OF PROJECT. This project will no longer be maintained by Intel. Intel will not provide or guarantee development of or support for this

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

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

scalene: a high-performance CPU and memory profiler for Python by Emery Berger 中文版本 (Chinese version) About Scalene % pip install -U scalene Scalen

pyinstrument Pyinstrument is a Python profiler. A profiler is a tool to help you 'optimize' your code - make it faster. It sounds obvious, but to get

Yappi Yet Another Python Profiler, but this time thread&coroutine&greenlet aware. Highlights Fast: Yappi is fast. It is completely written in C and lo

py-spy: Sampling profiler for Python programs py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spe

About cx_Freeze cx_Freeze creates standalone executables from Python scripts, with the same performance, is cross-platform and should work on any plat

Nuitka User Manual Contents Overview Usage Requirements Command Line Installation License Tutorial Setup and build on Windows Setup Install Python Ins

Overview docs tests package A pytest fixture for benchmarking code. It will group the tests into rounds that are calibrated to the chosen timer. See c

asn1crypto A fast, pure Python library for parsing and serializing ASN.1 structures. Features Why Another Python ASN.1 Library? Related Crypto Librari

scandir, a better directory iterator and faster os.walk() scandir() is a directory iteration function like os.listdir(), except that instead of return

srsly: Modern high-performance serialization utilities for Python This package bundles some of the best Python serialization libraries into one standa

django-watson django-watson is a fast multi-model full-text search plugin for Django. It is easy to install and use, and provides high quality search

Django Cachalot Caches your Django ORM queries and automatically invalidates them. Documentation: http://django-cachalot.readthedocs.io Table of Conte

Flask Monitoring Dashboard A dashboard for automatic monitoring of Flask web-services. Key Features • How to use • Live Demo • Feedback • Documentatio

Yandex Tank Yandextank has been moved to Python 3. Latest stable release for Python 2 here. Yandex.Tank is an extensible open source load testing tool

Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst

What's this This is a high performance python wsgi web server. And Meinheld is a WSGI compliant web server. (PEP333 and PEP3333 supported) You can als

The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou

The 3rd place solution for competition "Lyft Motion Prediction for Autonomous Vehicles" at Kaggle Team behind this solution: Artsiom Sanakoyeu [Homepa

cnn_age_gender Age and Gender prediction using Keras Dataset example : Description : UTKFace dataset is a large-scale face dataset with long age span

Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion

Rugby score prediction An end-to-end machine learning web app to predict rugby scores Overview An demo project to provide a high-level overview of the

asyncpg -- A fast PostgreSQL Database Client Library for Python/asyncio asyncpg is a database interface library designed specifically for PostgreSQL a

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a