Popular GitHub Repositories for Pipeline

A guideline for building practical production-level deep learning systems to be deployed in real world applications.

cube studio开源云原生一站式机器学习/深度学习/大模型AI平台，支持sso登录，大数据平台对接，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务VGPU，边缘计算，标注平台，自动化标注，大模型微调，vllm大模型推理，llmops，私有知识库，AI模型应用商店，支持模型一键开发/推理/微调，支持国产cpu/gpu/npu芯片，支持RDMA，支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/spark/ray/volcano分布式，deepseek训练推理

Machine Learning Pipelines for Kubeflow

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

Machine learning platform for Web developers

HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance

? Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications

A Julia machine learning framework

An open-source ML pipeline development platform

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

? LinGoose is a Go framework for building awesome AI/LLM applications.

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Library for clinical NLP with spaCy.

ML pipeline orchestration and model deployments on Kubernetes.

Simple and flexible ML workflow engine

Efficient ML solution for long-tailed demands.

A distributed backend AI pipeline server

Neural networks training pipeline based on PyTorch

Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.

MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization