MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web.

A DSL for data-driven computational pipelines

Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取，2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019

A Python Toolbox for Machine Learning Model Combination

Open solution to the Home Credit Default Risk challenge 🏡

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

Open solution to the Mapping Challenge 🌎

Function Composition for OpenFaaS

BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.

Open solution to the TGS Salt Identification Challenge

🔀 FluentMediator is an unobtrusive library that allows developers to build custom pipelines for Commands, Queries and Events.

Package strit introduces a new type of string iterator, along with a number of iterator constructors, wrappers and combinators.

Relational data pipelines for the science lab

CNStream is a streaming framework for building Cambricon machine learning pipelines http://forum.cambricon.com

Vent is a light-weight platform built to automate network collection and analysis pipelines using a flexible set of popular open source tools and technologies. Vent is python-based, extensible, leverages docker containers, and provides both an API and CLI.

Easy to use Pytorch

PyPPL - A Python PiPeLine framework.

Lightweight library for composing chain of responsibility pipelines

Open solution to the Google AI Object Detection Challenge 🍁

C++ library for defining and controlling modern GPU rendering/processing operations.

A lightweight, distributed workflow system

Open solution to the Santander Value Prediction Challenge 🐠

The General-Purpose Cross-Language Dataflow Programming

COMP Superscalar (COMPSs) is a framework which aims to ease the development and execution of applications for distributed infrastructures, such as Clusters, Grids and Clouds.

Curated set of transformers that make your work with steppy faster and more effective 🔭

Surround is a framework for building machine learning pipelines in Python, https://surround.readthedocs.io/en/latest/

A Node.js and JavaScript synchronous data pipeline processing, data sharing and stream processing library. Actionable & Transformable Pipeline data processing.

Fun functional programming with pipelinable functions

Function sequencing reloaded

Open solution to the TalkingData AdTracking Fraud Detection Challenge